Physically secure digital signal processing for blind differentially-spread wireless M2M networks

ABSTRACT

A method and apparatus for physically secure communication over machine-to-machine (M2M) networks is claimed, through the use of frequency-hop and random access spread spectrum modulation formats employing using truly random spreading codes and time/frequency hopping and receiver selection strategies at the transmitters in the M2M network, blind signal detection and linear signal separation techniques at the receivers in the M2M network, completely eliminating the ability for an adversary to predict and override M2M transmissions. Additional physical security protocols are also introduced that allow the network to easily detect and identify spoofing transmissions on uplinks and downlinks, and to automatically excise those transmissions as part of the despreading procedure, even if those transmissions are received at a much higher power level than the intended transmissions. Extensions to weakly and strongly macrodiverse networks are also described, which provide additional efficiency and security improvements by exploiting the route diversity of the network.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

FIELD OF THE INVENTION

The present invention relates generally to digital signal processing,with particular emphasis on machines wirelessly communicating with eachother (“machine to machine” or “M2M” intercommunication) in noisy,crowded, multiple-use and multiple-overlap environments. A majority ofthis wireless intercommunication may occur with indirect, remote, orotherwise removed human oversight focusing on the network and specificcommunications rather than implementing and effecting each, or even themajority, of such, as part of a broader intercommunication background ofmultiple networks of machines comprising what has been called “theinternet of things” or IoT. The environment for such wirelessintercommunication may be ‘noisy’ as there may be multiple, chaoticnetworks operating with different standards and disparate organization,often transmitting highly bursty, asymmetric traffic from many differentsources. Blind linear signal separating secure digital processingmethods can be used to provide physically secure wireless M2Mintercommunications in such environments, without direct humanmanagement, and in a manner that is robust, efficient, andinterference-resistant.

Signal generation for message and addressing content (respectively, the‘data’ containing the information to be communicated and ‘metadata’describing the sourcing, routing, and receiver for the message beingcommunicated) is no more to be confused with the specific signalsforming the message itself, than the process of combining letters andwords of a language into a message and delivering it to a recipient, arewith formation and delivery of meaning that that message conveys.

BACKGROUND OF THE INVENTION

Machine-to-machine (M2M) networks comprise a thick mesh of tieredhardware forming the skeleton and body of a communications network,incorporating as desired sensor-and-reporting elements, whicheffectively comprise a ‘nervous system’. Avoiding the time, expense, andeffort of physically installing, maintaining, and most particularlyadapting wired intercommunication linkages requires that the elementsuse wireless signals in any, or any set, of electromagnetic spectrumbands.

For any wireless network, providing feedback for regular, directed, andemergency reporting processes all are useful to its continuous operation(particularly when under stress or upon experiencing a failure, whetherpoint, localized, or central, with recovery desired both ‘as soon, andas safe, as possible’ or ‘AS, AAS, AP’).

At the ‘edges’ of the wireless network, every nodal point (home,building, or mobile station) may be a Signaling Machine (SM). Any finitenumber of Signaling Machines can be aggregated to a lesser order set ofData Aggregation Points (DAP's) each of which serving as an intermediatenetwork distribution point to provide a set of delivery paths with theirown capacity or divisibility indices; and these DAP's must also bemonitored to avoid unthinking overloads or under-utilizations. DAP's maythen transfer the signaling to a wired ‘trunk’ or background line; butthe communication between DAP and SM's may assuredly be in a ‘noisy’environment, for at least two readily foreseeable causes.

First, the physical environment of the SM's and DAP's may vary fromsub-cell (one DAP, many SM's) to the next, and even within the samesub-cell as vehicles move about, doors open and close, and otherphysical events occur. So there may be also issues of interference forthe network—both within one sub-cell (between SM's and their assignedDAP), and between sub-cells (from adjacent, i.e. geographically,immediately adjacent or overlapping) that are neighbors within theoverall network.

Second, the communication between DAP and SM's, in one embodimentoperates in the ISM band—which is a shared media. Other devices (e.g.smartphones, wireless printers, and computers) whose penetration andnumber are rapidly growing, and thus their message traffic, use the ISMband for their own purposes and with their own protocols, timing, andplacements that may be ever-changing and unpredictable.

To effect wireless communication under such conditions reliably andefficiently needs digital signal processing which can handle complex,noisy, ‘dirty’ and above all—uncontrolled and unpredictablyvarying—communication conditions. This is the background in which thepresent description takes form.

The principle areas in which M2M communications may take place include(but are not limited to: utility networks (electricity, water, naturalgas); industrial operations (as an obvious extension from the former,refineries; but also including manufacturing, distribution/logisticalprocessing, warehousing, and transshipment operations—particularly thoseswitching between modes of transport, e.g. rail-and-truck ortruck-and-ship); agricultural and pastoral production (large-scaleplanting, care, harvesting of grain, truck, or tree crops; or open- orclosed-range herds); transportation networks (riverine, includingbarge/lock/bridge interactions; seaborne in channels, harbors, straits,or other ‘narrows’; airborne (around or between terminals); and road(including ‘convoy’ or ‘aggregate’ vehicle groupings or clusters);healthcare (intra- and inter-provider operations, remote servicing andcommunications); education (also intra- and inter-provider operations,remote servicing, Massively On-Line Open Courses, reverse-pyramidtutorial schemes, ‘educational portal’ services); all aspects of valueexchange and financial transactions (credit, debit, swap; goods,services, or financial and other ‘intangibles’); and social media(ad-hoc peer narrow-, group-, peer-, or open-ended ‘casting’; messaging;social calendaring & coordination of ‘agents’). The similarity amongstthese areas include the following key aspects:

-   -   (a) Potentially high asymmetry between numbers of SM's at the        lowest tier or “edge” of the network, and DAP's at higher tiers        in the network.    -   (b) Potentially high asymmetry in uplink and downlink        transmission requirements between network tiers. In the most        extreme case (and, in one embodiment, an advantageous case for        this invention), SM's at the network edge may preferentially        communicate data units to DAP's without any need to requirement        for feedback from those DAP's, except for transport of        infrequent physical-layer (PHY) messages to set or reset        security protocols between the SM's and DAP's. Example services        that meet this criterion include User Data Protocol (UDP) and        Trivial File Transfer Protocol (TFTF) services.    -   (c) Potentially high asymmetry in cost, complexity,        size-weight-and-power (SWaP), and energy usage requirements        between (typically “dumb”) SM's at the network edge and DAP's at        higher tiers in the network.    -   (b) Transmission of small data bursts, rather than extensive        data-heavy, continuing linkages, with low average rate relative        to human-centric operational ‘norm’ at the respective time.    -   (d) Rapidly varying and highly dynamic variation in interference        observed by SM's and DAP's, comprising both interference        generated by the M2M network, and interference generated from        emitters operating ‘outside’ the M2M network.

An individual human may have multiple ‘terminals’ in such an M2Mnetwork—everything from physiological sensors in his clothing andaccessories, to multiple communications and information-processingdevices. An individual ‘origination point’ may be a single person, asingle machine, a single household, or a single building—with greater orlesser ‘interior’ differentiation and demands.

Power efficiency may be an important criterion for at least some membersof the network, as wireless operations may require self-sufficiency forextended periods at non-predictable intervals; without fixed wires,power is more likely to be provisioned by batteries with weight andcapacity limitations and thus be more expensive.

Additional important criteria for M2M networks and elements include:mobility, ubiquity, and minimization of maintenance costs (of servicing,of replacement elements, and of ‘opportunity of use’, i.e. downtime),especially at the network edge; and avoidance of network-centric SMauthentication, association, and provisioning requirements that canunduly load the network downlink and create critical points of failurein the network. In particular, the ability to operate with limited or“local” provisioning of security keys can greatly improve robustness andscalability of the network, and (if successfully implemented) eliminatecritical points of attack by adversaries seeking to corrupt or penetratethe M2M network.

All of the above criteria (and others known to the field but notspecifically described here) generally militate towards a least-costeconomic pressure; the networks that are pragmatically operable may bethose that can most readily adapt to such. Unlike critical-path, ‘mustsucceed’ operations, M2M communications may have to accommodatelocalized failures, environmentally-caused intermittency, and be able tofail and then recover. The elements and networks can tolerate lower datatransmission rates, transmission delays, and flawed communicationhandovers—using the principle benefit of machines, persistence and exactrepetition—to overcome transient faults. They need not be as perfect aspossible (in comparison to, say, a human-implanted medical supportdevice), as durable as manufacturable (in comparison to, say, amulti-decade geosynchronous-orbit communications satellite), or even assecure against failure as imaginable (in comparison, say, to a nuclearreactor's in-pile operational machinery). Yet M2M networks and thus theindividual elements therein must still be resistant (‘hardened’) againstboth inadvertent and intentional ‘spoofing’ effects (whether these arisefrom unintentional or intentional mistakes, environmentally-sourceddistortions, and sabotage). Continued public acceptance of this approachto M2M networks and their intercommunications requires sustainably highconfidence in the validity, verity, and non-distortability of suchnetwork's operations, for all SM's and DAP's, all of the time. Thesecurity of the network must be trusted even when real-world dangers, bethose mistakes or temporary failures, or intentional efforts tomisguide, intercept, spoof, or substitute network signals, are present.This security must be secured in and by the real world, rather thanexist solely in some perfect model or algorithmic abstraction.

At the present time there are no fixed standards for M2M wirelesscommunications networks that are universal, global, or national. Thereare cellular, Wi-Fi, and other ‘bands’ in the electromagnetic spectrumwhich might be used (and multiple combinations therein might be, also);and the distance ranges for such can shift from short, to close, to mid,to long range—crossing the boundaries of skin, clothing, walls, andgeography respectively.

Furthermore, because this is an evolving domain, changes can beanticipated to stay both rapid and continuing. Thus an open-ended,rather than closed, proprietary, solution may have the greatest utility.Changes may come to and from each and all of the use of the network, itsprovisioning and servicing capital (hardware and institutions), itsspectra of transmission and reception (‘transception’); and its mode ofinterstitial operation (amplitude, frequency, temporal, spatial, andother diversities of transmission and reception). Chief concerns mayinclude avoiding interference, using low-output power (if only to avoiddeafening itself with ‘white noise’ from such), and intelligentapplication, sensitive to both the environmental conditions andhuman-imposed restrictions and requirements (whether regulatory,operational, or standards-compliant).

SUMMARY OF THE INVENTION

The present invention is a method for wireless intercommunicationbetween a set of Signaling Machines (SM's) and a set of Data AggregationPoints (DAP's), comprising within a selected frequency range (in oneembodiment, the 902-928 MHz ISM band) a frequency-hop direct-sequence(FHDS) spread-spectrum modulation format, which provides cyclicchip-level and symbol-level cyclic prefixes to control channel multipathand interference loading, and which preferentially employs transmissioninformation that is randomly determined at every node in the network,and neither known to the receivers in the network nor provisioned by thenetwork. On the uplink, this randomly determined transmissioninformation includes:

-   -   the physical dwell (time slot and frequency channel) used by        each uplink transmit node in the network, which physical dwell        is randomly varied over every time frame;    -   the spreading code used by each uplink transmit node in the        network, which spreading code is also randomly varied over every        time frame; and    -   elements of a source symbol mask applied to the data bursts        prior to spreading, which source symbol mask is also randomly        varied over every time frame.

Additionally, if multiple uplink receivers are in the field-of-view(FoV) of the uplink transmitter and have pathloss communication withthose receivers, the uplink receiver selected by the uplink transmitnode can also be randomly varied over each time frame. On the downlink,this randomly determined transmission information includes:

-   -   the spreading code used by each downlink transmit node in the        network, which spreading code is randomly varied in every time        slot of each time frame; and    -   elements of a source symbol mask applied to the data bursts        prior to spreading, which source spreading mask is also randomly        varied over every time frame.

Additionally, each downlink transmit node in the network transmits overa downlink frequency channel that is preferentially pseudorandomlyvaried over each time slot of each frame, using an algorithm that isprovided to, known to, or learnable by each downlink receiver(s) allowedto communicate with that downlink transmit node, and which algorithm islocally and independently set at each downlink transmitter.

This randomly-determined transmission information can be provisioned atand by each transmitter, with each intended receiver being blind (nopre-set agreement or provisioning between transmitter and receiver) tothe choice of that transmission information, and using only rudimentaryprovisioning from any specific transmitter in the network to only itsset of intended receivers in the network of a commonly-known and sharedreceive symbol mask for all signals intended for a given receiver(s) soas to differentiate them from transmissions by that specific transmitterintended for other nodes in the network, as well as transmissions fromother transmitters in the network intended for that particularreceiver(s). The random spreading codes are further exploited at eachreceiver to differentiate between subsets of nodes transmitting to thesame or different receivers in the network, preferentially using lineardigital signal processing methods that can separate signals with widelyvarying receive power, and experiencing arbitrary channel multipath withgroup delay less than or equal to the cyclic prefix imposed during thespreading operation. This further permits the use of multiple time andfrequency coincident transmissions and also avoids provisioning overhead(which reduces data transmission rates) required by using matched-filterdespreading.

All of these enable higher security, by greatly complicating the taskfor any observer to determine actual in-use transmissions from noise; byeliminating the ability for an observer to predict the randomlydetermined transmission information used at the nodes in the network;and by using linear digital signal processing methods to exciseintruders from legitimate network transmissions. For example, even if anintruder has learned the uplink receive symbol mask, so that theintruder can pose as a legitimate uplink transmission, the intruder maynot be able to predict the randomly determined uplink transmissioninformation used by any uplink transmitter in the network; will not beable to consistently jam any uplink transmitter in the network; may beinstantly identified as a duplicated authorized node, or an unauthorizednode, by the uplink receiver, allowing the uplink receive symbol mask tobe reset by the system; and may in any event be excised by the lineardigital signal processing methods employed by the uplink receiver.

One embodiment has the network exploit these arbitrary spreading codes,enabling this method to be used in any ad-hoc (not previouslydesignated) set of SM's and DAP's, requiring only the preliminarycommonalization (i.e. provisioning, of the symbol mask to the set ofSM's and DAP's forming the ad-hoc network); and this method can beemployed in any FDMA, TDMA, FHMA or OFDMA (Frequency Diverse MultipleAccess; Time Diverse Multiple Access, Frequency Hop Multiple Access,Orthogonal Frequency Diverse Multiple Access) network without schedulingof intercommunications, thereby reducing the feedback response overheadcost. Because the despreading algorithms are not required to bepre-arranged, hard-coded, or otherwise communicated throughout thenetwork, but can be least-common-knowledge shared, fully-blind innature, they present the lowest overhead for any such approach, do notrequire carrier synchronization, and enable the SM's and DAP's (thenetwork) to operate without either knowledge of a carrier offset or‘handshake’ overhead signaling.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated in the attached presentationexplaining some aspects of the present invention, which includeSignaling Machine networks (SM's and DAP's) working under various‘loads’ of interfering, same-band signals from non-network sources aswell as potentially-interfering within-network signals from the sets ofSM's and DAP's.

FIG. 1 is a drawing of overlapping and non-cooperatingmachine-to-machine (M2M) transceivers operating in an exemplarymedium-range network, with each sub-network, or cell, containingmultiple SM's connecting with a single DAP.

FIG. 2 is a drawing of overlapping and non-cooperating medium-range M2Mnetworks, each with multiple SM's connecting to a single DAP, showingthe interference between multiple networks.

FIG. 3 is a drawing of overlapping and non-cooperating medium-range M2Mnetworks, each with multiple SM's connecting to a single DAP, showingthe interference from out-of-network devices.

FIG. 4 is a drawing of overlapping and non-cooperating medium-range M2Mnetworks, each with multiple SM's connecting to a single DAP, with anadditional intrusive element shown respectively attempting to eavesdropon, intercept, or interfere with, a network.

FIG. 5 is a drawing of overlapping and non-cooperatingmachine-to-machine (M2M) transceivers operating in the long-range M2Mnetwork, in which a large number of low-complexity M2M transceivers arecommunicating with a small number of higher-complexity M2M transceivers.

FIG. 6 is a drawing of the time-frequency structure and parameters ofeach ‘frame’ used in the Cyclic-Prefix Direct-Sequence (CPDS) systemembodiment for the long-range M2M network shown in FIG. 5.

FIG. 7 is a drawing of the hardware implementation at each cyclic-prefixDirect-Sequence (CPDS) uplink transmitter used in the long-range M2Mnetwork embodiment.

FIG. 8 is a drawing of the logical and computational processes performedin each time frame to self-provision network resources used by the CPDSuplink transmitter shown in FIG. 7.

FIG. 9 is a drawing of the hardware implementation at each cyclic-prefixDirect-Sequence (CPDS) downlink transmitter used in the long-range M2Mnetwork embodiment. This Figure includes the logical and computationalprocesses performed in each time slot to self-provision networkresources used by the CPDS downlink transmitter.

FIG. 10 is a drawing of the logical and computational processes thatimplement the Cyclic-Prefix Direct-Sequence (CPDS) Spreader (in oneembodiment, comprising digital signal processing hardware) for eachuplink transmitter used in the long-range M2M network embodiment shownin FIG. 5, and for time-frequency framing structure shown in FIG. 6.

FIG. 11 is a drawing of the logical and computational processes thatimplement the CPDS Spreader (again, in one embodiment, comprisingdigital signal processing hardware) for each downlink transmitter usedin the long-range M2M network embodiment shown in FIG. 5, and for thetime-frequency framing structure shown in FIG. 6.

FIG. 12 is a drawing of the logical and computation processes thatinsert a symbol mask onto the baseband data stream input to the CPDSspreader. This Figure furthermore shows the criteria for adding thatsymbol mask directly to the baseband data in the ‘time domain’, or tothe data in the ‘frequency domain’ via incorporation of discrete Fouriertransform (‘DFT’) and inverse DFT (‘IDFT’) operations.

FIG. 13 shows finer detail of the spreading of the signal within thestructure on the exemplary CPDS uplink.

FIG. 14 shows the finer detail of the spreading of the signal within thestructure during a downlink.

FIG. 15 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element for modifying the coding.

FIG. 16 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element for setting the dwell index.

FIG. 17 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element by which elements of the sourcesymbol mask, e.g., a cyclic frequency offset, are generated randomly.

FIG. 18 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element by which the intended uplinkreceiver is selected randomly from a set of candidate uplink receiversover every time frame in a randomizer element and then provided to theCPDS uplink spreader.

FIG. 19 is a drawing of the hardware implementation at eachcyclic-prefix Direct-Sequence (CPDS) uplink receiver used in thelong-range M2M network embodiment.

FIG. 20 is a drawing of the hardware implementation at each CPDSdownlink receiver used in the long-range M2M network embodiment.

FIG. 21 is a drawing of the CPDS despreading procedure implemented (inany combination of hardware and software elements) on eachtime-frequency channel accessed by an uplink receiving device in thenetwork.

FIG. 22 is a drawing of the CPDS despreading procedure implemented (inany combination of hardware and software elements) on each time-slotaccessed by a downlink receiving device in the network.

FIG. 23 describes the procedure used to adapt the CPDS despreader in oneembodiment.

FIG. 24 is a drawing of the computational and logical processes used toperform CPDS despreading if a cyclic symbol prefix is added to the CPDStransmit signal and the observed path delay at the CPDS receiver isgreater than the duration of the cyclic chip prefix.

FIG. 25 is a drawing of the hardware and processing steps used in oneembodiment to perform weakly-macrodiverse CPDS despreading.

FIG. 26 is a drawing of the hardware and processing steps used in oneembodiment to perform strongly-macrodiverse CPDS despreading.

FIG. 27 is a drawing of the time-frequency structure and parameters ofeach ‘frame’ used in the alternate Frame Synchronous (FS) systemembodiment for the long-range M2M cell shown in FIG. 5.

FIG. 28 is a drawing of the hardware implementation of the uplinktransmitter employed in an alternate embodiment whereby an uplink signalstream is sent through a Frame-Synchronous (FS) Spreader.

FIG. 29 is a drawing of the hardware implementation of the downlinktransmitter employed in an alternate embodiment whereby a downlinksignal stream is sent through a Frame-Synchronous (FS) Spreader.

FIG. 30 is a drawing of the logical and computational processes thatimplement the alternate Frame Synchronous (FS) Transmitter Structure (inan alternate instantiation of the alternate embodiment, comprisingdigital signal processing hardware) for each uplink transmitter used inthe long-range M2M network embodiment shown in FIG. 5, and for thetime-frequency framing structure shown in FIG. 27.

FIG. 31 is a drawing of the logical and computational processes thatimplement the alternate Frame Synchronous (FS) Spreading Structure (inan alternate instantiation of the alternate embodiment, comprisingdigital signal processing hardware) for each downlink transmitter usedin the long-range M2M network embodiment shown in FIG. 5, and for the902-928 MHz time-frequency framing structure shown in FIG. 27.

FIG. 32 shows finer detail of the spreading of the signal within thestructure on an exemplary alternate FS uplink.

FIG. 33 shows finer detail of the spreading of the signal within thestructure on an exemplary alternate FS downlink.

FIG. 34 is a drawing of a possible hardware implementation at each framesynchronous (FS) uplink receiver used in the alternate long-range M2Mnetwork embodiment.

FIG. 35 is a drawing of a possible hardware implementation at each framesynchronous (FS) downlink receiver used in the alternate long-range M2Mnetwork embodiment.

FIG. 36 is a drawing of the FS despreading procedure implemented (in anycombination of hardware and software elements) on each time-frequencychannel accessed by an uplink receiving machine in the network in analternative embodiment.

FIG. 37 is a drawing of the FS despreading procedure implemented (in anycombination of hardware and software elements) on each time-slotaccessed by a downlink receiving machine in the network in analternative embodiment.

DETAILED DESCRIPTION OF THE DRAWINGS

FIG. 1, in one embodiment, is the drawing of overlapping andnon-cooperating machine-to-machine (M2M) transceivers operating in anexemplary medium-range network, with each sub-network, or cell,containing multiple SM's (1) connecting with a single DAP (2).Connections between the DAP's (2) or with any other part of a network,are not shown but are not excluded.

FIG. 2, in one embodiment, is the drawing of overlapping andnon-cooperating medium-range M2M networks, each with multiple SM's (1)connecting to a single DAP (2), showing the interference (the dottedlines) between multiple networks (specifically, adjacent-cellinterference).

FIG. 3, in one embodiment, is the drawing of overlapping andnon-cooperating medium-range M2M networks, each with multiple SM's (1)connecting to a single DAP (2), showing the interference from or without-of-network devices (emitters (3) or receivers (4), respectively).

FIG. 4, in one embodiment, is the drawing of overlapping andnon-cooperating medium-range M2M networks, each with multiple SM's (1)connecting to a single DAP (2), with at least one additional intrusiveelement attempting to intercept (and potentially spoof in a‘man-in-the-middle’ attack) (5), eavesdrop on or monitor (6), orinterfere with (7), a network.

FIG. 5, in one embodiment, is the drawing of overlapping andnon-cooperating machine-to-machine (M2M) transceivers (‘nodes’)operating in the long-range M2M network, in which a large number oflow-complexity M2M transceivers are communicating with a small number ofhigher-complexity M2M transceivers; with this drawing showing anexemplary application for this network: a wireless, Smart Grid, edgenetwork, in which the low-complexity M2M nodes are Smart Meters (SM's)(8) and the higher-complexity M2M transceivers (‘Nodes’) are DataAggregation Points (DAP's) (9). It is assumed that the low-complexityM2M nodes (8) are at a lower elevation restricting their view to a smallnumber of higher-complexity Nodes (9), similar to user equipment (‘UE’s)in a cellular telephony network, and that the low-complexity M2M nodes(8) have identified a primary or “nearest neighbor” higher-complexityM2M Node (9) in the network. However, it is not assumed that thelow-complexity M2M nodes (8) are restricted to, or even preferentiallytransmit to that primary higher-complexity Node (9).

FIG. 6, in one embodiment, is the drawing of the time-frequencystructure and parameters of each ‘frame’ used in the preferredCyclic-Prefix Direct-Sequence (CPDS) system embodiment for thelong-range M2M cell shown in FIG. 5, shows how on the uplink, each SmartMachine (SM) intending to transmit data to a Data Aggregation Point(DAP) in a 4 second frame first randomly selects one of 5,000 physicaltime-frequency dwells, comprising 100 contiguous 40 ms physical timeslots (10) covering the 4 second frame (11), and frequency-channelizedinto 50 contiguous 500 kHz physical frequency channels (12) covering 25MHz of the 902-928 MHz ISM band. The SM then transmits its intendedinformation over a 30 ms uplink (UL) subslot (13) of that time-frequencydwell using a signal employing a cyclic-prefix Direct-Sequencemodulation format. On the downlink, over each 30 ms time slot, each DAPselects one (14) of the 50 physical frequency channels (12) using apseudorandom selection algorithm known to its intended SM's. The DAPthen broadcasts its intended information over a 9.675 ms downlink (DL)subslot (15) of that frequency channel. Each time slot has an additional75 μs UL-to-DL guard interval (16) to allow timing advancement of the SMUL transmissions to its primary (but not necessarily preferential) DAP,and a 250 μs DL-to-UL guard interval (17) to prevent DAP-to-DAPinterference from the DAP DL transmissions. Each frequency channel hasan additional set-aside of ±50 kHz guard band to account for carrierlocal oscillator (‘LO’) uncertainty and power amplifier (‘PA’)intermodulation distortion (‘IMD’) in the transmitted SM and DAPsignals. This framing structure allows the SM's and DAP's to be fullycompliant with FCC § 15.247 regulation for frequency-hop spread spectrumintentional radiators in the 902-928 MHz band. However, the framingstructure shown in FIG. 6 can be used with any long-range M2M network inwhich a large number of low-complexity M2M transceivers arecommunicating with a small number of higher-complexity M2M transceiversin a manner that is compliant with 902-928 MHz ISM band emissionrestrictions.

FIG. 7, in one embodiment, is the drawing of the hardware implementationat each cyclic-prefix Direct-Sequence (CPDS) uplink transmitter used inthe long-range M2M network embodiment. The information to be sent in theintended transmission passes from a baseband encoder (20) successivelyto the CPDS spreader (21), the raised-root cosine (‘RRC’) interpolationpulse and pulse-amplitude modulator (‘PAM’) (22), and into at least onedigital-to-analog converter (‘DAC’) (in one embodiment, dual converters)(23). A source transmit start time (‘t_(S)’) for each time frame(‘n_(frame)’) (24) is sent to the clock (25) which is both connected tothe DAC (23) and the LO (26), which also receives a selected sourcetransmit center frequency (‘f_(S)’) for each time frame n_(frame) (27).From the DAC the now-analog signal is sent through the at least one LPF(28) (in one embodiment, dual LPF's are used) and then to theupconverter (29), which also takes the frequency-specific input from theLO (26). The upconverter (29) then sends the converted digital signal tothe power amplifier PA (31), which also receives a power setting(‘P_(S)(n_(frame))’) for each time frame n_(frame) (30), from where thetransmission becomes a wireless signal.

FIG. 8, in one embodiment, is the drawing of the logical andcomputational processes performed in each time frame to self-provisionnetwork resources used by the CPDS uplink transmitter shown in FIG. 7,showing that information is taken from a database of geolocations forboth source and candidate uplink receivers (40) and then used to computethe best timing advance to the ‘nearest’ (which may measure not justgeographic separation, but Quality of Signal, least-interference,least-problematic multipath, or other alternate values) uplink receiver(42); that the selection of the dwell index (43) of k_(dwell)(n_(frame))inputs into the calculation of a mapping (44) of k_(dwell)(n_(frame)) tothe correct time slot index k_(slot)(n_(frame)) and frequency channelindex k_(chan)(n_(frame)), with the correct slot being combined with theframe index n_(frame) to generate the transmit start time (45) whichthen is used with the best timing advance to calculate (46) the slotstart time for each frame index n_(frame), t_(S)(n_(frame)) (24) (whichin FIG. 7 is shown sent to the clock). The frequency channel indexk_(chan)(n_(frame)) is used to compute (47) both the source transmitcenter frequency for each n_(frame), f_(S)(n_(frame)) (27) (which inFIG. 7 is shown sent to the LO), and also along with information takenfrom a database of candidate uplink receivers (48) from which theintended uplink receiver(s) for each frame index n_(frame),l_(R)(n_(frame)) is(are) selected (49), combined to set the sourcetransmit power setting for each n_(frame), P_(S)(n_(frame)) (30) (whichin FIG. 7 is shown sent to the PA).

In one embodiment, FIG. 9, the drawing of the hardware implementation ateach cyclic-prefix Direct-Sequence (CPDS) downlink transmitter used inthe preferred long-range M2M network embodiment, includes the logicaland computational processes performed in each time slot toself-provision network resources used by the CPDS downlink transmitter.In this downlink transmitter, differentiating it from the uplinktransmitter described and shown in FIG. 7, instead of a timing signalfor each frame, a network time synchronization (51) for the slot starttime at each slot index n_(slot), t_(S)(n_(slot)), is given to the clock(25), and for each slot index n_(slot) and uplink transmitter sourceindex l_(S) the frequency channel index k_(chan)(n_(slot)) is firstdetermined (52) and then used to select the source transmit centerfrequency (47) which is fed to the LO (26).

In one embodiment, FIG. 10, the drawing of the logical and computationalprocesses that implement the Cyclic-Prefix Direct-Sequence (CPDS)Spreader (21) (in one embodiment, comprising digital signal processinghardware) for each uplink transmitter used in the long-range M2M networkembodiment shown in FIG. 5, and for the 902-928 MHz time-frequencyframing structure shown in FIG. 6, shows that the CPDS spreader uses amodulation-on-symbol spreading format, in which a spreading code isrepeated over each baseband symbol transmitted over a slot. In addition,the spreading structure includes incorporation of cyclic prefixes inboth the spreading code and the baseband symbol stream to mitigatemultipath and delay uncertainty between the transmitter and receiver inthe network; and multiplication of the baseband symbols by a symbol maskthat provides PHY security to the signal.

For each frame, from both the intended receiver index l_(R)(n_(frame))and physical dwell index k_(dwell)(n_(frame)) are used to generate itsreceive symbol mask (60) which in one embodiment takes the form ofM_(sym)×1 vector m_(R)(n_(frame),k_(dwell)(n_(frame))) to which agenerated source symbol mask (61) of the form of M_(sym)×1 vectorm_(S)(n_(frame)) is combined (62), producing the symbol mask of the formof M_(sym)×1 m_(RS)(n_(frame)) formed by the element-wise (Schur)productm _(RS)(n _(frame))=m _(R)(n _(frame) ,k _(dwell)(n _(frame)))∘m _(S)(n_(frame));to which the converted baseband source symbol stream b_(S)(n_(sym)),after serial-to-parallel (S/P) conversion (63) to M_(sym)×1 sourcebaseband vector

b_(S)(n_(frame)) = [b_(S)(n_(frame)M_(sym) + n_(sym))]_(n_(sym) = 0)^(M_(sym) − 1)for frame n_(frame) , has applied on a framewise basis for eachn_(frame) (64), producing M_(sym)×1 source data vector d_(S)(n_(frame)),to which the cyclic symbol prefix is added (65) thus producing N_(sym)×1extended source data vector d_(S)(n_(frame)); and a code is generatedfor each n_(frame) (66), to which the cyclic chip prefix is applied(67), producing N_(chp)×1 spreading code vector c_(S)(n_(frame)) foreach n_(frame); after which the twin streams with applied cyclicprefixes are combined (68) producing the N_(chp)×N_(sym) source signalmatrix S_(S)(n_(frame)) of the formS _(S)(n _(frame))=c _(S)(n _(frame))d′ _(S)(n _(frame));which is then fed to N_(chp)×N_(sym):1 Matrix/Serial converter (69) toproduce the source signal stream s_(S)(n_(chp)) (70).

FIG. 11, in one embodiment, is the drawing of the logical andcomputational processes that implement the CPDS Spreader (again, in onepreferred embodiment, comprising digital signal processing hardware) foreach downlink transmitter used in the preferred long-range M2M networkembodiment shown in FIG. 5, and for the time-frequency framing structureshown in FIG. 6 (which in one embodiment is 902-928 MHz), differschiefly from FIG. 10 in that the transformations are for each time slotn_(slot) rather than each time frame n_(frame).

FIG. 12, in one embodiment, is the drawing of the logical andcomputation processes that insert the symbol mask (64) onto the basebanddata stream input to the CPDS spreader, and furthermore shows thecriteria for adding that symbol mask directly to the baseband data inthe ‘time domain’, or to the data in the ‘frequency domain’ viaincorporation of discrete Fourier transform (‘DFT’) and inverse DFT(‘IDFT’) operations. In this Figure, the frame and dwell indices shownin FIG. 10 for the uplink spreader parameters are not shown, but areunderstood to be present; and the slot index shown in FIG. 11 for thedownlink spreader parameters are not shown, but are understood to bepresent. The M_(sym)×1 source baseband vector b_(S) is first passedthrough a switch (71), which determines the manner in which the symbolmask is to be inserted. On the upper path (connecting the switch (71) tomultiplier element (72)), the M_(sym)×1 symbol mask m_(RS) is applieddirectly to M_(sym)×1 source baseband vector b_(S) in the ‘time domain’using an element-wise multiplication operation (72), resulting inM_(sym)×1 source data vector d_(S) given by d_(S)=m_(RS)∘b_(S), where“∘” denotes the element-wise or Schur matrix product operation. On thelower path (connecting the switch (71) to the ‘DFT’ element (73), theM_(sym)×1 symbol mask m_(RS) is applied to the M_(sym)×1 source basebandvector b_(S) in the ‘frequency domain’, by applying an M_(sym)-pointdiscrete Fourier transform (DFT) operation to b_(S) (73), resulting inM_(sym)×1 source baseband subcarrier vector B_(S); applying m_(RS) toB_(S) using an element-wise multiplication operation (74), resulting inM_(sym)×1 source data subcarrier vector D_(S)=m_(RS)∘B_(S); and applyingan M_(sym)-point inverse DFT (IDFT) to D_(S) (75), resulting inM_(sym)×1 source data vector d_(S).

Preferentially, the symbol mask is applied to the source baseband vectorin the ‘time domain’ if a cyclic symbol prefix is not inserted in to thesource data vector (step (65) shown in FIG. 10 or FIG. 11), i.e., if thecyclic symbol prefix duration K_(sym)=N_(sym)−M_(sym)=0, and the symbolmask is applied to the source baseband vector in the ‘frequency domain’if the cyclic symbol prefix is inserted in to the source data vector,i.e., if the cyclic prefix duration K_(sym)>0. However, it should beunderstood that either insertion method, or any other insertion methodthat allows the symbol mask to be easily removed at the despreader, canbe employed in one embodiment by the embodiments in the presentdescription and that the switch (71) can be interpreted as an actualoperation that is explicitly instantiated in the transmitter, or as achoice of insertion methods that can be implemented at the transmitterin one instantiation or another. It should also be understood that theDFT operation (73) can also be dispensed with if the source basebandvector b_(S) is itself defined in the ‘frequency domain,’ e.g., as thesubcarriers of an OFDM or OFDM-like modulation format.

FIG. 13, the drawing of the finer detail of the spreading of the signal(68) within the structure on the exemplary CPDS uplink, shows how in oneembodiment as exemplary Uplink Parameters, it uses 480 symbols, has nocyclic prefix, has 16 symbols/ms for a 30 ms UL hop dwell/slot;incorporates a 20-chip inner spreading code (effecting thereby a 320chips/ms chip-rate) and for that has a 4-chip (12.5 ms) cyclic prefix.This would enable, for the network, some 20 separable SM's for each DAP,with an observed delay less than 12.5 μs, tolerating a 3.75 km pathspread with timing advancement to the nearest DAP of 10 km cells.

In one embodiment, FIG. 14, the drawing of the finer detail of thespreading of the signal (68) within the structure during a downlink,shows how in one embodiment, as exemplary downlink Parameters, it uses384 symbols, incorporates a 3 symbol (75 μs) cyclic prefix, 40symbols/ms for a 9.675 ms DL hop dwell/slot, incorporates an 8-chipinner spreading code (320 chips/ms chip-rate), and for that has nocyclic prefix (loading accepted). This may enable, for the network,between 4-to-8 DAP's separable for each SM using time-channelizeddespreading with an observed 6 dB power reduction possible (−6 dBE_(c)/N_(o) BPSK threshold at capacity).

In one embodiment, FIG. 15, the drawing showing a CPDS-enabled networkelement with a real-world, random-number, sourcing-sensor element formodifying the coding, shows how the real-world, random-number, sourcingsensor (76) provides a truly random kernel input using real-world chanceevents which is used to generate a random seed (777) from which thespreading code is generated randomly over every transmit opportunity(every time frame n_(frame) on the uplink, and every time slot n_(slot)on the downlink); applying this to a code vector (78) and then adding acyclic chip prefix (67) then provided to the CPDS spreader (21), therebyproviding physical, or ‘reality-based’ security rather than algorithmicor model-based security.

In one embodiment, FIG. 16, the drawing showing a CPDS-enabled networkelement with a real-world, random-number, sourcing-sensor element forsetting the dwell index, shows how the real-world, random-number,sourcing sensor (76) provides a truly random kernel input usingreal-world chance events which is used to generate a random seed (77)which is used to set the dwell index (81) for each frame which is thenmapped over slot and channel indices (44) which are then provided to theCPDS uplink transmitter, again providing physical, or ‘reality-based’security rather than algorithmic or model-based security.

In one embodiment, FIG. 17, the drawing showing a CPDS-enabled networkelement with a real-world, random-number, sourcing-sensor element thatprovides a truly random kernel input from a sourcing sensor usingreal-world chance events (76) from which elements of the source symbolmask, e.g., a cyclic frequency offset, are generated randomly, shows howthe generated random seed (77) is used to generate the source symbolmask (83), along with the intended uplink receiver index at framen_(frame)(l_(R)(n_(frame))) and physical time-frequency dwell index atframe n_(frame)(k_(dwell)(n_(frame))) which are combined to generate thereceive symbol mask (60), and then the two symbol masks (source andreceive) are combined (62) with the result then provided to the CPDSuplink spreader, again providing physical, or ‘reality-based’ securityrather than algorithmic or model-based security.

In one embodiment, FIG. 18, the drawing showing a CPDS-enabled networkelement with a real-world, random-number, sourcing-sensor element thatprovides a truly random kernel input from a sourcing sensor usingreal-world chance events (76) from which the intended uplink receiver isselected randomly from a set of candidate uplink receivers, shows howthe generated random seed (77) is used to select the uplink receiver atframe n_(frame)(l_(R)(n_(frame))) (49), which is used along with thephysical time-frequency dwell index at framen_(frame)(k_(dwell)(n_(frame))) to generate the receive symbol mask(60), which is combined (62) with the source symbol mask (83), and whichis further used along with the channel frequency index at framen_(frame)(k_(chan)(n_(frame))) to set the source transmit power at framen_(frame)(P_(S)(n_(frame))) (30) from a database of transmit powersrequired to close the link to the intended uplink receiver (50), againproviding physical, or ‘reality-based’ security rather than algorithmicor model-based security.

In one embodiment, FIG. 19, the drawing of the hardware implementationat each cyclic-prefix Direct-Sequence (CPDS) uplink receiver used in thepreferred long-range M2M network embodiment, shows whereby the incomingreceived signal-in-space is received by at least one antenna andlow-noise amplifier (‘LNA’) (90), down-converted to complex basebandrepresentation (91) ((in-phase and quadrature analog waveforms) using alocal oscillator (‘LO’) (95) tuned to a single frequency(preferentially, the center of the network), whereby the in-phase andquadrature analog waveforms are filtered using a dual lowpass filter(‘LPF’) (92), sampled at a rate (driven by clock (94)) preferentiallysufficiently high enough digitize the entire network bandwidth withoutaliasing using a dual analog-to-digital convertor (‘ADC’) (93), anddigitally demultiplexed into physical time-frequency dwells (separatedinto time slots and frequency channels) accessible to the receiver (96);and whereby each physical dwell is passed through an uplink CPDSdespreader (97), modified with a feedback loop through an adaptationalgorithm (98), and each resulting symbol stream is fed through to asymbol demodulator (99) that incorporates the frequency offset estimatesalso provided by the adaptation algorithm for environmentaldelay/degradation effects actually observed by the receiving machine.

In one embodiment, FIG. 20, the drawing of the hardware implementationat each CPDS downlink receiver used in the long-range M2M networkembodiment, shows whereby the incoming received signal-in-space isreceived by at least one antenna and LNA (90), down-converted to complexbaseband representation (91) using an LO (95) tuned on each time slotn_(slot) to the center of the known frequency channel used by thedownlink transmitter on that slot, f_(R)(n_(slot)), and digitized usingdual LPF (92) and dual ADC (93) operations over that time slot; andwhereby that time slot of data is passed through the downlink CPDSdespreader (97) (modified with a feedback loop through an adaptationalgorithm (98)), and the resulting symbol stream is fed through to asymbol demodulator (99) that incorporates the frequency offset estimatesalso provided by the adaptation algorithm for environmentaldelay/degradation effects actually observed by the receiving machine.

FIG. 21, in one embodiment, is the drawing of the CPDS despreadingprocedure (97) of FIG. 19 implemented (in any combination of hardwareand software elements) on each time-frequency channel accessed by anuplink receiving machine in the network, if the symbol mask is appliedto the baseband source data in the time domain as shown in the uppersymbol mask insertion path in FIG. 12, preferentially performed if thecyclic symbol prefix duration is equal to 0(K_(sym)=0).

The ^(N) _(smp)N_(sym)-sample received signal sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1)output from the dwell demultiplexer (shown in FIG. 19, element (96))over dwell k_(dwell) and time frame n_(frame) (where N_(sym) is thenumber of source data symbols transmitted in the dwell and N_(smp) isthe number of demultiplexer output samples per source data symbol) isdespread by the steps of:

-   -   Performing a 1:N_(smp)×N_(sym) serial/matrix conversion (110) on        the demultiplexer output signal sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1),and removing the K_(smp)-sample cyclic chip prefix and (if applied atthe transmitter) the K_(sym)-symbol cyclic symbol prefix from theN_(smp)×N_(sym) matrix resulting from that serial/matrix conversionoperation (111), resulting in M_(smp)×M_(sym) received signal matrixX_(R)(n_(frame),k_(dwell)), given mathematically by

$X = \begin{pmatrix}{x\left( {{N_{smp}K_{sym}} + K_{smp}} \right)} & \ldots & {x\left( {{N_{smp}\left( {N_{sym} - 1} \right)} + K_{smp}} \right)} \\\vdots & \ddots & \vdots \\{x\left( {{N_{smp}K_{sym}} + N_{smp} - 1} \right)} & \ldots & {x\left( {{N_{smp}\left( {N_{sym} - 1} \right)} + N_{smp} - 1} \right)}\end{pmatrix}$

-   -   for general received data sequence

{x(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1),and where K_(smp)=N_(smp)×M_(smp) is the number of demultiplexer outputsamples covering the cyclic chip prefix.

-   -   Removing the M_(sym)×1 receive symbol mask vector        m_(R)(n_(frame),k_(dwell)) mask vector over dwell k_(dwell) and        time frame n_(frame) from the received signal matrix        X_(R)(n_(frame),k_(dwell)) (112), given mathematically by        X _(R)(n _(frame) ,k _(dwell))←X _(R)(n _(frame) ,k        _(dwell))diag{m* _(R)(n _(frame) ,k _(dwell))}    -   where diag{•} is the vector-to-diagonal matrix conversion        operation and (•)* is the complex conjugation operation,        resulting in M_(smp)×M_(sym) demasked signal matrix        X_(R)(n_(frame),k_(dwell)).    -   Perform a linear combining operation on demasked signal matrix        (113), given mathematically by        {circumflex over (D)} _(R)(n _(frame) ,k _(dwell))=W _(R)(n        _(frame) ,k _(dwell))X _(R)(n _(frame) ,k _(frame)),    -   where W_(R)(n_(frame),k_(dwell)) is an L_(port)×M_(smp) linear        combining matrix, computed as part of the adaptation procedure        shown in FIG. 23, that substantively despreads the source        symbols transmitted to the receiver over dwell k_(dwell) and        time frame n_(frame), and to which the symbol mask        m_(R)(n_(frame),k_(dwell)) has been inserted, resulting in        L_(port)×M_(sym) despread symbol matrix {circumflex over        (D)}_(R)(n_(frame),k_(dwell)).    -   Apply M_(sym):1 parallel-to-serial (P/S) conversion operation        (114) to each column of {circumflex over        (D)}_(R)(n_(frame),k_(dwell)), resulting in 1×L_(port) despread        symbol sequence vectors

{d̂_(R)(n_(sym); n_(fram), k_(dwell))}_(n_(sym) = 0)^(M_(sym) − 1).

FIG. 22, in one embodiment, is the drawing of the CPDS despreadingprocedure (97) of FIG. 20 implemented (in any combination of hardwareand software elements) on each time-slot accessed by a downlinkreceiving machine in the network; and differs chiefly from FIG. 21 inthat the transformations are for each time slot n_(slot) rather thaneach time frame n_(frame).

FIG. 23, in one embodiment, shows the procedure used to adapt the uplinkdespreader (97) shown in FIG. 21, and at the downlink despreader (97)structure shown in FIG. 22, by:

-   -   1^(st): Detecting all sources intended for the receiver,        estimating key parameters of those signals, and developing        linear combining weights that can substantively despread the        source symbols, said operations comprising:        -   1.A computing the QR decomposition (QRD) of the            M_(smp)×M_(sym) received signal X_(R), resulting after            removal of cyclic prefix(es) (111) and the receive symbol            mask (112);        -   1.B generating an SINR/carrier revealing feature spectrum            that can (i) estimate the maximum attainable despread            signal-to-interference-and-noise ratio (‘maximum despreader            SINR’) of each signal impinging on the receiver that is            employing the receive symbol mask (‘authorized signals’),            given the received spreading code (source spreading code,            modulated by the transmission channel) of each signal and            interference impinging on the receiver at the dwell and            time-frame being monitored by the receiver, (ii) as a            function of observed frequency offset of that signal,            and (iii) provide statistics that can be used to develop            linear combining weights that can substantively achieve that            max-SINR, without knowledge of the received spreading code            for any of those signals, and without knowledge of the            background noise and interference environment;        -   1.C detecting L_(port) significant peak(s), in the            SINR/carrier revealing feature spectrum, and determining the            maximum despreader SINR and frequency offset of each peak;        -   1.D refining strengths (estimated maximum despreader SINR)            and locations (estimated frequency offsets) of each            significant peak, e.g., using Newton search methods; and        -   1.E developing L_(port)×M_(smp) linear combiner weight            matrices W_(R) that can substantively achieve the maximum            despreader SINR for each authorized signal, without            knowledge of the received spreading code for any of those            signals, and without knowledge of the background noise and            interference environment.    -   Then:    -   2^(nd): Despreading and demodulating the detected sources, said        operations comprising:        -   2.A Substantively despreading the sources detected in Step            1.C, by multiplying the demasked signal matrix provided at            the output of (112) in FIG. 21 and FIG. 22 by the            substantively despreading linearly combining linear combiner            weights computed in Step 1.E, said matrix multiplication            operation shown in element (113) in FIG. 21 and FIG. 22.        -   2.B Substantively remove frequency offset from the despread            symbols, using the frequency offset estimates computed in            Step 1.D.        -   2.C Estimate and correct phase offsets, and further refine            frequency offsets to algorithm ambiguity using known            features of the source symbols, e.g., adherence to known            symbol constellations, unique words (UW's) and training            sequences embedded in the source symbols, known properties            of the source symbol mask, etc.;        -   2.D Remove algorithm ambiguity using additional features of            the source symbols, e.g., UW's, forward error correction            (FEC), cyclic redundancy check's (CRC's), etc.; and        -   2.E Decrypt traffic and protected medium access control            (MAC) data.    -   Then:    -   3rd: Perform ancillary processing as needed/appropriate:        -   3.A Compute received incident power (RIP) for open-loop            power control, using SINR and channel estimates provided by            the CPDS despreading algorithm (uplink receiver);        -   3.B Correlate source internals, externals with trusted            information, using dwell, intended receiver and source            symbol mask elements provided by the CPDS receiver and            despreading algorithm; and        -   3.C Detect network intrusions—revise symbol masks if needed            (downlink receiver).

FIG. 24, in one embodiment, is the drawing of the CPDS despreadingprocedure implemented (in any combination of hardware and softwareelements) on each time-frequency channel accessed by an uplink receivingmachine in the network, if the symbol mask is applied to the basebandsource data in the frequency domain as shown in the lower symbol maskinsertion path in FIG. 12, preferentially performed if the cyclic symbolprefix is greater than 0(K_(sym)>0) . The N_(smp)N_(sym)-sample receivedsignal sequence

{x_(R)(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1)input to the despreader is despread by the steps of:

-   -   Passing

{x_(R)(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1)through a 1:N_(smp)N_(sym) serial-to-parallel (S/P) converter (115), andremoving the first K_(sym) symbols (N_(smp)K_(sym) samples) encompassingthe cyclic symbol prefix from the resultant N_(smp)N_(sym)×1 S/P outputvector (116), resulting in N_(smp)M_(sym)×1 received data vector x_(R).

-   -   Performing a N_(smp)M_(sym)-point discrete Fourier transform        (DFT) operation (117) on x_(R) (thereby converting it to the        ‘frequency domain’); reshaping the N_(smp)M_(sym)×1 DFT output        vector into an N_(smp)×M_(smp) matrix using a 1:M_(sym) S/P        converter and matrix transpose operation (118), resulting in        N_(smp)×M_(sym) received data matrix X_(R).    -   Removing the M_(sym)×1 receive symbol mask vector m_(R) mask        vector from X_(R) (112), given mathematically by        X _(R) ←X _(R)diag{m* _(R)}    -   where diag{•} is the vector-to-diagonal matrix conversion        operation and (•)* is the complex conjugation operation,        resulting in N_(smp)×M_(sym) demasked signal matrix X_(R).    -   Perform a separate linear combining operation to each column of        demasked signal matrix X_(R) (119), given mathematically by        {circumflex over (D)} _(R)(:,k _(sym))=W _(R)(k _(sym))X        _(R)(:,k _(sym)), k _(sym)=0, . . . , M _(sym)−1,    -   where W_(R)(k_(sym)) is an L_(port)×M_(smp) linear combining        matrix, computed as part of the adaptation procedure shown in        FIG. 23, that substantively despreads the DFT bin (‘subcarrier’)        k_(sym) of each of the source symbols detected by the receiver,        and to which the symbol mask m_(R) has been inserted, resulting        in L_(port)×M_(sym) despread symbol subcarrier matrix        {circumflex over (D)}_(R).    -   Apply M_(sym):1-point inverse DFT (IDFT) to each row of        {circumflex over (D)}_(R) (120), and M_(sym):1        parallel-to-serial (P/S) conversion operation (114) to each        column of the resultant IDFT output matrix, resulting in        L_(port)×1 despread symbol sequence vectors

{d̂_(R)(n_(sym))}_(n_(sym) = 0)^(M_(sym) − 1).

FIG. 25, in one embodiment, is the drawing of the hardware andprocessing steps used in one embodiment to perform weakly-macrodiverseuplink CPDS despreading. The uplink receiver performs the same uplinkreception, dwell demultiplexing, and adaptive despreading operationsshown in FIG. 19; the same uplink despreading operations shown in FIG.21 or FIG. 24 (depending on how the symbol mask is inserted as shown inFIG. 12); and the same despreader adaptation procedure shown in FIG. 23.However, the CPDS network employs a common receive symbol mask (122) ata set of L_(R)>1 uplink receivers in the network, such that theM_(sym)×1 receive symbol mask m_(R)(n_(frame),k_(dwell);l_(R)) used overphysical dwell k_(dwell) in time frame n_(frame) at each uplink receiver

{l_(R)}_(l_(R) = 1)^(L_(R))in that set is identical, i.e.,m_(R)(n_(frame),k_(dwell);l_(R))≡m_(R)(n_(frame),k_(dwell)) for everyreceiver in that set.

At uplink receiver l_(R) used for weakly-macrodiverse uplinkdespreading, and if the symbol mask is inserted into the baseband sourcesymbols using the time-domain method shown on the upper path of FIG. 12,each signal sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1)output from the dwell demultiplexer (96) is passed through aserial/matrix converter (110) and a matrix thinning operation to removethe cyclic prefixes from the serial/matrix converted symbol matrix(122), and the common receive symbol mask is removed from the resultantdata matrix using the multiplicative operation (112) shown in FIG. 21,resulting in M_(smp)×M_(sym) demasked data matrixX_(R)(n_(frame),k_(dwell);l_(R)). The demasked data matrix is thenadaptively despread using the linear combining operation shown in FIG.21 (113), and using the despreader adaptation procedure shown in FIG. 23(123), which detects L_(port) sources using the common receive mask;computes an L_(port)×1 frequency offset vector

α̂_(R)(n_(frame), k_(dwell); l_(R)) = [α̂_(R)(n_(frame), k_(dwell); l_(port), l_(R))]_(l_(port) = 1)^(L_(port))where {circumflex over (α)}_(R)(n_(frame),k_(dwell);l_(port),l_(R)) isan estimate of the frequency offset of the signal detected on portl_(port); estimates and substantively despreads the signal detected oneach output port, resulting in L_(port)×M_(sym) despread data matrix{circumflex over (D)}_(R)(n_(frame),k_(dwell);l_(R)).

The despread data matrix and frequency offset vector from every uplinkreceiver engaged in weakly-macrodiverse despreading is then uploaded toa central site (125), where the signal ports from each such receiver aresorted by dwell, frequency offset estimate, and other sourceobservables, e.g., cross-correlation properties and known symbol fields,e.g., Unique Words, to associate signals detected at each port with thesame source (126), and each sorted source is demodulated into sourcesymbol estimates using a multidimensional demodulation algorithm (127).

If the symbol mask is inserted in the frequency domain, as shown on thelower path of FIG. 12, then the serial/matrix conversion operation (110)and the cyclic prefix(es) removal operation (121) shown in FIG. 25 arereplaced by the serial/parallel conversion (115), cyclic symbol prefixremoval (116), DFT (117) and serial-to-parallel conversion, andtransposition (117) operations shown in FIG. 24, and the frequencyoffset estimates and despread data matrix output from thecolumn-by-column linear combining (119) and IDFT (120) operations isuploaded to the central site (125).

FIG. 26, in one embodiment, is the drawing of the hardware andprocessing steps used in one embodiment to perform strongly-macrodiverseCPDS despreading. The CPDS network employs the same common receivesymbol shown in FIG. 25 mask for a set of L_(R)>1 uplink receivers inthe network, and performs the same operations shown in FIG. 25 togenerate M_(smp)×M_(sym) demasked data matrixX_(R)(n_(frame),k_(dwell);l_(R)) after removal of that common receivesymbol mask (122). The entire demasked data matrix is then uploaded to acentral site (125), where it is stacked with the demasked data matricesuploaded from every other receiver using that common receive symbol mask(128), to form L_(R)M_(smp)×M_(sym) network data matrixX_(R)(n_(frame),k_(dwell)) given by

$\begin{matrix}{{{X_{R}\left( {n_{frame},k_{dwell}} \right)} = \begin{pmatrix}{X_{R}\left( {n_{frame},{k_{{{dwe};};};1}} \right)} \\\vdots \\{X_{R}\left( {n_{frame},{k_{dwell};L_{R}}} \right)}\end{pmatrix}},} & ({Eq1})\end{matrix}$

The network data matrix is then passed to a network-level despreader(97), which employs the adaptation procedure (98) shown in FIG. 23 todetect L_(port) sources using the common receive mask; computes anL_(port)×1 frequency offset vector

α̂_(R)(n_(frame), k_(dwell)) = [α̂_(R)(n_(frame), k_(dwell); l_(port))]_(l_(port) = 1)^(L_(port)),where {circumflex over (α)}_(R)(n_(frame),k_(dwell);l_(port)) is anestimate of the frequency offset of the signal detected on portl_(port); and compute L_(port)×M_(smp)L_(R) linear combiner weightsW_(R)(n_(frame),k_(dwell)). Those weights are then used to despread thestacked receive data vector (97), resulting in L_(port)×M_(sym) despreaddata matrix {circumflex over (D)}_(R)(n_(frame),k_(dwell)). It should benoted that the number of output ports L_(port) achievable at the centralsite can be much higher than the number of output ports achievable atany single site, due to the higher number of linear combiner ‘degrees offreedom’ M_(smp)L_(R) available in the stacked receive signal matrix.

In one embodiment, FIG. 27, the drawing of the time-frequency structureand parameters of each ‘frame’ used in the alternate Frame Synchronous(FS) system embodiment for the long-range M2M cell shown in FIG. 5,shows the framing structure similar to the CPDS framing structure shownin FIG. 6, except in this embodiment the durations of the DL subslots(131) are 9 ms, and the preceding and following guard intervals (130,132) are each 500 μs. This framing structure again allows the SM's andDAP's to be fully compliant with FCC § 15.247 regulation forfrequency-hop spread spectrum intentional radiators in the 902-928 MHzband. However, these much higher guard intervals allows the alternate FSnetwork to be used in applications where the SM's and/or DAP's arecommunicating over much longer ranges or at much higher altitudes, e.g.,in airborne or satellite communication networks. In addition, this framestructure provides sufficient guard interval to eliminate the need forSM timing advancement in many applications.

In one embodiment, FIG. 28, the drawing of the hardware implementationof the uplink transmitter employed in an alternate embodiment whereby anuplink signal stream is sent through a Frame-Synchronous (FS) Spreader(136), is structurally the same as the CPDS uplink transmitter shown inFIG. 7, except that the FS embodiment does not integrate the basebandmodulation and spreading operations, but instead directly spreadsbaseband signals using any baseband modulation format (135).

In one embodiment, FIG. 29, the drawing of the hardware implementationof the downlink transmitter employed in an alternate embodiment wherebya downlink signal stream is sent through a Frame-Synchronous (FS)Spreader 136), is structurally the same as the CPDS downlink transmittershown in FIG. 9, except that the FS embodiment does not integrate thebaseband modulation and spreading operations, but instead directlyspreads baseband signals using any baseband modulation format (135).

FIG. 30, in one embodiment, is the drawing of the logical andcomputational processes that implement the alternate Frame Synchronous(FS) Transmitter Structure (in the instantiation of the alternateembodiment of the FS spreader (136) of FIG. 28, comprising digitalsignal processing hardware) for each uplink transmitter used in thelong-range M2M network embodiment shown in FIG. 5, and for the 902-928MHz time-frequency framing structure shown in FIG. 27. N_(DAC)-samplebaseband source sequence d_(S)(n_(DAC)) intended for transmission overtime-frame n_(frame) is first passed to a 1:N_(DAC) serial-to-parallel(S/P) convertor (143) resulting in N_(DAC)×1 source symbol vector

d_(S)(n_(frame)) = [d_(S)(n_(frame)N_(DAC) + n_(DAC))]_(n_(DAC) = 0)^(N_(DAC) − 1).The source symbol vector is then spread over time (144) using anN_(chp)×1 spreading code vector c_(RS)(n_(frame)), mathematically givenbyS _(S)(n _(frame))=d _(S)(n _(frame))c _(RS) ^(T)(n _(frame)),resulting in N_(DAC)×N_(chp) data matrix S_(S)(n_(frame)), followed byan N_(DAC)×N_(chp):1 matrix-to-serial conversion operation (145) toconvert S_(S)(n_(frame)) to a (N_(DAC)N_(chp))-chip scalar data streams_(S)(n_(DAC)), in which each column of S_(S)(n_(frame)) is seriallyconverted to a scalar data stream, moving from left to right across thematrix.

This Figure also shows c_(RS)(n_(frame)) being constructed from theelement-wise multiplication (142) of an N_(chp)×1 source spreading codec_(S)(n_(frame)) (140) that is unique to the uplink transmitter andrandomly varied between time frames, and an N_(chp)'1 receive spreadingcode c_(R)(n_(frame),k_(dwell)(n_(frame))) (141) that is pseudorandomlyvaried based on the time frame n_(frame), the physical dwellk_(dwell)(n_(frame)) employed by the receiver over time frame n_(frame),and the intended uplink receiver l_(R)(n_(frame)). However, if thebaseband source vector has known or exploitable structure, the entirecode vector can be constructed locally using random spreading code.

FIG. 31, in one embodiment, is the drawing of the logical andcomputational processes that implement the alternate Frame Synchronous(FS) Spreading Structure (in one instantiation of the alternateembodiment of the FS spreader (136) of FIG. 29, comprising digitalsignal processing hardware) for each downlink transmitter used in thelong-range M2M network embodiment shown in FIG. 5, and for the 902-928MHz time-frequency framing structure shown in FIG. 27, differs chieflyfrom FIG. 30 in that the transformations are for each time slot n_(slot)rather than each time frame n_(frame).

In one embodiment, FIG. 32, the drawing showing finer detail of thespreading of the signal within the structure on an exemplary alternateFS uplink, shows how in this embodiment as exemplary Uplink Parameters,it employs a baseband OFDM signal modulation with a 1.5 ms symbol periodincluding a 250 μs cyclic prefix (1.25 ms FFT duration, or 0.8 kHzsubcarrier separation), allowing transport of 480 subcarriers in 384 MHzof active bandwidth, effecting thereby a 16 symbol/ms in-dwellinformation symbol rate; and incorporates a 20-chip outer spreadingcode, enabling each DAP in the network to detect, despread, and separateup to 20 SM emissions intended for that DAP, or to excise as many as 19SM emissions intended for other DAP's in the network. In addition, thecyclic prefix employed by the baseband modulation format provides up to250 μs of group delay tolerance, equivalent to a 75 km path spread. Thispath spread is sufficient to eliminate the need for timing advancementof the uplink transmitters in the long-range communication applicationdescribed in FIG. 5.

In one embodiment, FIG. 33, the drawing showing finer detail of thespreading of the signal within the structure on an exemplary alternateFS downlink, shows how in this embodiment as exemplary DownlinkParameters, it employs the same baseband modulation format as the uplinkspreader, allowing transport of 480 subcarriers in 384 MHz of activebandwidth, effecting thereby a 16 symbol/ms in-dwell information symbolrate; and incorporates a 6-chip outer spreading code, enabling each SMin the network to detect, despread, and separate up to 6 DAP emissions,or to excise as many as 5 DAP emissions intended for other SM's in thenetwork. The cyclic prefix employed by the baseband modulation formatagain provides up to 250 μs of group delay tolerance, equivalent to a 75km path spread.

In one embodiment, FIG. 34, the drawing of a possible hardwareimplementation at each frame synchronous (FS) uplink receiver used inthe alternate long-range M2M network embodiment, shows whereby theincoming received signal-in-space is received at antenna(e),down-converted from the analog incoming waveforms, and demultiplexedinto physical dwells (96) accessible to the receiver; and whereby eachphysical dwell is passed through an uplink FS despreader (147) (modifiedwith a feedback loop through an adaptation algorithm (149) to detect andsubstantively despread the FS signals received on each dwell), and eachresulting substantively despread signal stream is fed through to abaseband demodulator (148), is structurally the same as the CPDS uplinkreceiver shown in FIG. 19, except that the FS embodiment does notintegrate the baseband symbol demodulation operations, but insteaddespreads baseband signals using any baseband modulation format.

In one embodiment, FIG. 35, the drawing of a possible hardwareimplementation at each frame synchronous (FS) downlink receiver used inthe alternate long-range M2M network embodiment, differs chiefly fromFIG. 34 in that the transformations are for each time slot n_(slot)rather than each time frame n_(frame).

In one embodiment FIG. 36, the drawing of the logical and computationalprocesses that implement the alternate Frame Synchronous (FS) DespreaderStructure (147) of FIG. 34 (in one instantiation of the alternateembodiment, comprising digital signal processing hardware) for eachuplink receiver used in the long-range M2M network embodiment shown inFIG. 5, show despreading of the demultiplexed uplink data sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1)received in k_(dwell) over time frame n_(frame) by performing thesequential steps of:

-   -   Performing a 1:N_(smp)×N_(chp) serial-to-matrix conversion        operation (154) on the demultiplexer output signal sequence        resulting

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1),resulting in N_(smp)×N_(chp) matrix X_(R)(n_(frame),k_(dwell)), givenmathematically by

$X = \begin{pmatrix}{x(0)} & \ldots & {x\left( {N_{smp}\left( {N_{chp} - 1} \right)} \right)} \\\vdots & \ddots & \vdots \\{x\left( {N_{smp} - 1} \right)} & \ldots & {x\left( {{N_{smp}\left( {N_{chp} - 1} \right)} + N_{smp} - 1} \right)}\end{pmatrix}$

-   -   for general received data sequence

{x(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1).

-   -   Removing the N_(chp)×1 receive spreading code        c_(R)(n_(frame),k_(dwell)) from X_(R)(n_(frame),k_(dwell))        (155), given mathematically by        X _(R)(n _(frame) ,k _(frame))←X _(R)(n _(frame) ,k        _(frame))diag{c* _(R)(n _(frame) ,k _(frame))}    -   where diag{•} is the vector-to-diagonal matrix conversion        operation and (•)* is the complex conjugation operation.    -   Computing N_(smp)×L_(port) despread baseband signal matrix        Y_(R)(n_(frame),k_(dwell)) (156), given mathematically by        Y _(R)(n _(frame) ,k _(dwell))=X _(R)(n _(frame) ,k _(frame))W        _(R)(n _(frame) ,k _(dwell)),    -   where W_(R)(n_(frame),k_(dwell)) is an N_(chp)×L_(port) linear        combining matrix computed using the procedure shown in FIG. 23.    -   Converting the despread baseband signal matrix        Y_(R)(n_(frame),k_(dwell)) back to a sequence of 1×L_(port)        despread baseband signal vectors        {y_(R)(n_(smp);n_(frame),k_(dwell))}_(n) _(smp) ₌₀ ^(N) ^(smp)        ⁻¹ by applying an N_(smp):1 parallel-to-series (P/S) conversion        operation (157) to each row of Y_(R)(n_(frame),k_(dwell)).

In one embodiment, FIG. 37, the drawing of the logical and computationalprocesses that implement the alternate Frame Synchronous (FS)Despreading Structure (147) of FIG. 35 (in one instantiation of thealternate embodiment, comprising digital signal processing hardware) foreach downlink receiver used in the long-range M2M network embodimentshown in FIG. 5, and for the 902-928 MHz time-frequency framingstructure shown in FIG. 27, differs chiefly from FIG. 36 in that thetransformations are for each time slot n_(slot) rather than each timeframe n_(frame).

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

While this invention is susceptible of embodiment in many differentforms, there is shown in the drawings and will herein be described indetail several specific embodiments with the understanding that thesespecific embodiments of the present disclosure are to be considered asindividual exemplifications of the principles of the invention and notintended to limit the invention to the embodiments illustrated.

The embodiments described herein presume a hardware implementation thatuses a single antenna per transceiving element, to which any of a set ofspatial excision/separation methods of digital signal processing may beapplied, including: Linear demodulators (which provide the benefits,among others, of low complexity, simpler network coordination); blindand/or uncalibrated adaptation algorithms; and Subspace-constrainedpartial update (SCPU) (in order to minimize adaptation complexity). In afurther embodiment, more than one antenna may be used and additionaldimensions of diversity (spatial, polarization, or any combinationsthereof) thus enabled, applied to the excision/separation/security DSP.

The embodiments further provide physical security as an intended butancillary benefit to overall network efficiency, as the method enablesany or all of the following in individual elements, sub-sets ofelements, or the entire set comprising the network, while sendingmessages: Pseudorandom or truly random spreading to prevent exploitationof compromised codes; Fast code replacement (“code hopping”) to preventexploitation of detected codes; and Low-power transmission modes tominimize detect footprint, defeat remote exploitation methods.

There are further network enhancements as an intended ancillary benefit,which include: Coordinated/simultaneous SM uplink transmission, DAPreception; the Elimination/enhancement of slotted ALOHA, TDMA protocols;Reduced interference presented to co-channel users; and Provableimprovement using information theoretic arguments. Plus, the overalleffect enables the network to function with both Blind/uncalibrated SMdownlink reception and, consequently, the elimination/minimization ofnetwork coordination (and the required signal overhead to effect thesame) at each SM.

In one embodiment, a method is provided for wireless intercommunicationbetween at least one Signaling Machine (‘SM’) and one Data AggregationPoint (‘DAP’) each belonging to a set of like devices (all capable ofboth transmitting and receiving) and with all said devices belonging tothe same network of which each said device is a node. Because thismethod is extremely flexible and adaptable, as described herein allembodiments disclosed in the present description must be understood tobe used by collections of devices where members of a specific collectionmay be both like (e.g. multiple SM's in Collection A) and disparate (asingle DAP also in Collection A). Intercommunication may be between afirst node and a second node, or a single node and multiple nodes, ormultiple nodes to single node, or multiple nodes to multiple nodes. Soat least one SM and at least one DAP may intercommunicate; likewise,more than one SM with a single DAP, more than one DAP with a single SM,multiples of SM's with multiples of DAP's; and SM's may intercommunicatewith other SM's and DAP's may intercommunicate with other DAP's, in anycombination. Each SM and DAP may be referred to as a ‘node’, a ‘device’,and (depending on their current activity and role) may be thetransmitter, receiver, or transmitter and receiver of a message (orintercommunication, or intended transmission); but calling the device atransmitter (or receiver) for its functional activity at the time, isnot usage to be confused with and taken as, requiring or stating thatthe device as a whole be solely that specific electronic component.

The FHDS spread-spectrum modulation is effected through spreading codes,and its format comprises time slots and frequency channels which combineto form a ‘time frame’; so the time slots and frequency channels aresub-divisions of the time frame. Any transmission may comprise at leastone time frame (and probably more), an uplink and a downlink, andcomprise both at least one data burst (a time period of activetransmission) and at least one guard interval (a time period of notransmission) (as seen in FIGS. 6 and 27). Transmissioninformation—which is not the content of the transmission, but itsstructure, nature, recipient(s), spreading code(s), and other such‘metadata’—may be not provisioned by the network nor known to thereceivers in the network, but locally determined, by any device for itsintended sub-set of other devices to which the transmission is to beintercommunicated. This transmission information may be any ofprovisioned, pseudorandomly selected, and randomly selected, by thetransmitting device and varied, likewise.

As one embodiment of the method uses blind fully-despreading algorithmsat each receiver, the network can implement arbitrary spreading codes(to distinguish intercommunications between each SM and DAP, or sub-setsor sets thereof); and these arbitrarily spreading codes can be chosenrandomly, pseudorandomly, or locally (that is, without coordination oractivation/change effort on the part of the network as a whole, i.e.without centralized network provisioning).

Furthermore, and equally importantly to the continued security, evenwhen, while, or after any attempted infiltration or interception, theselection of arbitrarily spreading codes actually used within thenetwork as a whole can be altered (again randomly, pseudorandomly, andlocally) with any timing and by any ad-hoc redivision of the network,thereby preventing any third party from learning, or predicting, andthus gaining access to, the intercommunications between any sub-set ofSM's and their DAP's. By using the spreading codes to differentiateintended signaling between the SM's and DAP, this method prevents mutualinterference amongst its elements.

To obtain the kernel for implementing a truly randomized spreading code,in at least one further embodiment the network incorporates at least onereal-world sensor which takes input from events in the real world as thesource for random-number generation (a real-world, random-number,sourcing sensor, or ‘RW-RN-SS’). For example, the network may have anamplitude sensor which picks the most powerful signal within a timeframe; or a photovoltaic sensor which detects the intensity of a lightshining through a set of heat-variant-density liquid containers (‘lavalamps’), or a frequency sensor which selects the mean, average, peak orlow, or other calculated value, of all frequencies detected within acertain time period. The method can then be using, during saidtransformations, input from a real-world, random-number, sourcing-sensorelement that provides a truly random kernel using real-world chanceevents for randomly effecting the transmission transformation, includingany combination of the following set: by randomly generating thespreading code over every transmit opportunity (every frame on theuplink, and every time slot on the downlink) in a randomizer element andthen providing the generated spreading code to the CPDS spreader; byrandomly generating the physical dwell index (time slot and frequencychannel) over every time frame in a randomizer element and thenproviding said randomly generated physical dwell index to the CPDSuplink transmitter; by randomly generating elements of the source symbolmask, e.g., a cyclic frequency offset, over every time frame in arandomizer element and then providing said randomly generated physicaldwell index; and, by randomly selecting an intended uplink receiver froma set of candidate uplink receivers over every time frame and thenproviding that selection of uplink receiver to the CPDS uplink spreader.

Thus the environment as a whole—including the ‘noise’ of all othertransmissions—can become a self-sourcing aspect of the network'ssecurity, using genuinely random and constantly-changing real-worldevents instead of a mere ‘pseudorandom noise’ (‘PN’) element.

In another and further embodiment each DAP incorporates in itself aRW-RN-SS to generate for that DAP and its associated SM's, the trulyrandomized spreading code(s) used by that subset of the network.

In yet another and further embodiment each SM incorporates in itself aRW-RN-SS to generate for that SM, the truly randomized spreading code(s)used by it.

Furthermore, the successful interception and detection of one spreadingcode does nothing to ensure further, continued, or future interceptionof any messages (within the affected sub-set of the network, or any partor whole of the network. As soon as the intercepted spreading code ischanged the new messages may be once again not merely encrypted, butbecome part of the overall ‘noise’ of the total environment.

As a consequence, the method completely eliminates the ability for anadversary to predict or control when, where in frequency, or even whoman SM may transmit to at any time. In the worst case scenario where theanti-spoofing protocols are compromised, an adversary can at bestgenerate a duplicate node that is easily detected and identified by thenetwork using PHY observables (e.g. carrier offsets, locational angles,intensity variations, timing inconsistencies, multipath imbalances, etc.as known to the state of the art, which in a transmission may be thePhysical Layer (‘PHY’) data bits), internals, or other trustedinformation possessed by the true SM and DAP. Whenever a node isduplicated the original source and intended recipient can, eachindependently or together, compare any of the PHY observables in thereceived transmissions and use any discrepancy from previously observedvalues to identify the adversarial node; and then ignore thatnow-identified hostile node, alert the other nodes in the network to thepresence, and PHY observable characteristics, of that now-identifiedhostile node, and otherwise respond.

One embodiment enables randomized and/or decentralized time-frequencyhopping and code spreading to defeat interception/deception attacks thatfocus on scheduled transmissions (including, among others, the‘man-in-the-middle’ interception type of attack). Indeed, one embodimenteliminates the very existence of feedback paths needed to scheduleuplink transmissions, thereby negating a critical point of attack forintruders attempting to intercept, jam, spoof, or otherwise disrupt thenetwork, as well as reducing downlink network loading imposed by thosepaths.

Further still, another embodiment also differs from the prior art inimplementing physical security which neither depends on every elementhaving an antennae array, nor which inherently exploits channeldifferences resulting from differing geographical placement of thosearrays, yet which allows both signaling between a SM and a DAP (or a‘user’ and a ‘base station’) and a pair of SM's or a pair of DAP's withthe same physical security and processing implementation, and withoutnetwork-assigned differentiation of processing methods.

One embodiment focuses on Max-SINR rather than matched-filterdespreading, uses fully-blind rather than parametric despreading, andemploys conventional LMMSE (Linear Minimum Mean-Squared SpreadingError), because this method greatly reduces the overhead to the network(signal-controlling and signal-defining sub-content) of itstransmissions, which correspondingly increases the efficiency andcapacity of the network. It also enables a back-compatible approach (toexisting communication signal, e.g. 802.11 DSSS) whenever and whereverdesired, enabling cost-effective implementation as signal/noisedensities become problematic, rather than an ‘entirely new generation’implementation effort where the entire network must be simultaneouslyupgraded as a prerequisite to the attainable improvement(s).

A further embodiment combines cyclic time prefixes and specific guardintervals that allow operation of any SM's-DAP network (or sub-portion),in an environment with very coarse time synchronization, without anysignificant loss of signal density or range of effectiveness.

In one embodiment the method fits each transmission into a series offrames of Upload (‘UL’) and Download (‘DL’) transmissions (FIG. 6). Eachframe comprises a frame structure with a 4-second frame period and 25MHz frequency bandwidth within the 902-928 MHz ISM band, divided into5,000 physical time-frequency dwells, comprising 100 contiguous 40 msphysical time slots covering the 4 second frame, andfrequency-channelized into 50 contiguous 500 kHz physical frequencychannels. Each physical time-frequency dwell is further subdivided intoa 30 ms UL subslot in which an SM can transmit to a DAP; a 9.675 ms DLsubslot in which a DAP can transmit to an SM; a 75 μs UL-to-DL guardinterval between the UL and DL subslots to allow timing advancement ofthe SM UL transmissions to its primary (but not necessarilypreferential) DAP, and a 250 μs DL-to-UL guard interval between the endof the DL subslot and the next time slot to prevent “DAP-to-DAPinterference” caused by DAP DL transmission into the next time slot.Each 500 kHz frequency channel has an additional set-aside of ±50 kHzguard band to account for carrier LO uncertainty and PA intermodulationdistortion (IMD) in the transmitted SM and DAP signals.

This frame structure enables a Point-to-Multipoint (‘P2MP’) transmissionthat is compliant with ‘intentional radiator’ exceptions under the FCC §15.247 requirements for the 902-928 MHz band. Moreover, the DL isbroadcast from the DAP, thereby avoiding the Point-Multi-Point (‘P-MP’)restriction and making it compliant with FCC § 15.247 requirements forthe 902-928 MHz band.

In one embodiment, the network used a method incorporating into eachtransmission at each transceiver a Cyclic-Prefix Direct-Sequence (CPDS)modulation-on-symbol spreader and fully-blind despreader within eachphysical time-frequency channel, thus providing a differentiator forthat transmission, with time-channelized despreading at the receiver, tofurther support the robustness and quality of the differentiation ofsignal from noise within the accepted transmission band. Furthermore,this spreading format incorporates randomization features that alsoeliminates the need for pre-deployment network planning and enables andallows more robust (mesh, macrodiverse) network topologies, improvingand increasing the stability and robustness of the actually deployednetwork. A reasonable estimate is that this multiplies the potentialcapacity for the network by a factor of 3, compared to conventional FHDSnetworks; or allows link connection at 10-20 dB lower power level withthe same fidelity. Using a single-carrier prefix also minimizes signalloading due to multipath or in-cell group delay. In one embodiment themethod may also be fitting each transmission into a series of frames ofUpload Transmissions (‘UpLink’) and Download Transmissions (‘DownLink’),and transmitting from the SM on any UpLink and from the DAP on anyDownLink.

In one embodiment, in the CPDS uplink transmitter shown in FIG. 7,information intended for transmission in a single physicaltime-frequency dwell of each frame (in accordance with FIG. 6) is firstpassed through baseband encoding algorithms, e.g., to add medium accesscontrol (MAC) and Physical layer (PHY) data bits, perform dataencryption and source/channel coding, and interleaving/scramblingoperations, convert bits to symbols, and add other PHY signatures (e.g.,training preambles and/or Unique Words) as needed/desired to simplifyreceive processing and/or eliminate processing ambiguities. This processcreates baseband source symbol stream b_(S)(n_(sym)) output from theencoder (20) at each symbol index n_(sym) utilized by the transmitter.

The baseband source symbol stream is then passed to the cyclic-prefixdirect-sequence (CPDS) spreading processor (21) shown in FIG. 10(described in detail below), thereby segmenting it into M_(sym)-symbolsource data segments and modulating each source data segment to generatespread source data stream; and outputting s_(S)(n_(chp)) output from theCPDS spreader (21) at each chip index n_(chp). Taking eachs_(S)(n_(chp)) output the method is subsequently pulse-amplitudemodulating (PAM) it by a raised-root-cosine (RRC) interpolation pulse(22); and converting this result to an analog signal-in-space (SiS).This transforms the digital stream to an analog transmission signal by,e.g., using a dual digital-to-analog convertor (DAC) (23) applied to thein-phase and quadrature rail (real and imaginary part) of the spreaddata stream; upconverting (29) this resulting analog SiS to a desiredsource frequency f_(S)(n_(frame)) (27) selected by the uplinktransmitter within time-frame n_(frame); and transmitting it at sourcetime t_(S)(n_(frame)) (24) selected by the uplink transmitter withintime-frame n_(frame), at a power level P_(S)(n_(frame)) (30) that isstrong enough to allow the intended uplink receiver l_(R)(n_(frame)) todetect, despread, and demodulate the uplink transmission.

As shown in FIG. 8, the source transmit time t_(S)(n_(frame)) andtransmit frequency f_(S)(n_(frame)) are preferentially selected randomlywithin each frame, by randomly selecting dwell index (43)k_(dwell)(n_(frame)) for that frame; mapping (44) k_(dwell)(n_(frame))to time slot k_(slot)(n_(frame)) and frequency channelk_(chan)(n_(frame)), and selecting t_(S)(n_(frame)) fromk_(slot)(n_(frame)) and f_(S)(n_(frame)) from k_(chan)(n_(frame)) via alook-up table. In particular, k_(dwell)(n_(frame)) is chosen without anyprior scheduling or coordination between the uplink transmitter and theuplink receivers in the network. So the method is selecting randomly thesource transmit time and transmit frequency f_(S)(n_(frame)) within eachframe, by randomly selecting dwell index k_(dwell)(n_(frame)) for thatframe, without any prior scheduling or coordination between the uplinktransmitter and the uplink receivers in the network; mappingk_(dwell)(n_(frame)) to time slot k_(slot)(n_(frame)) and frequencychannel k_(chan)(n_(frame)); and selecting t_(S)(n_(frame)) fromk_(slot)(n_(frame)) and f_(S)(n_(frame)) from k_(chan)(n_(frame)) via alook-up table.

Preferentially, in one embodiment, the uplink transmitter also usesknowledge of the range between itself and its nearest physical receiver,e.g., based on known geolocation information of itself and the uplinkreceivers in its field of view, to provide timing advancement sufficientto allow its transmission to arrive at that receiver at the beginning ofits observed uplink subslot. It should be noted that the nearestphysical receiver does not need to be the receiver that the uplinktransmitter is intending to communicate with. Additionally, this timingadvancement does not need to be precise to a fraction of a chip period;however, it should be a small fraction of the cyclic prefix used on theuplink.

Preferentially, in one embodiment, the source transmit powerP_(S)(n_(frame)) is calculated using an open-loop algorithm, e.g., bycalculating pathloss between each DAP in the SM's field of view duringdownlink subslots, and using that pathloss estimate to calculate powerrequired to determine the source power required to detect, despread, anddemodulate subsequent uplink transmissions. The source transmit powerdoes not need to precisely compensate for the pathloss between thetransmitter and receiver, but should have sufficient margin to overcomeany effects of fading between the uplink and downlink subslots,including processing gain achievable by the despreader in the presenceof credible numbers of other uplink transmissions. Additionally, thispower calculation is used to develop a database of candidate uplinkreceivers to which the transmitter can communicate without violating FCC§ 15.247 requirements for the 902-928 MHz band.

In alternate embodiments, this algorithm can be improved usingclosed-loop algorithms that use feedback from the uplink receiver toadjust the power level of the transmitter. Preferentially, in oneembodiment, the closed-loop algorithm should be as simple as possible,in order to reduce vulnerability to “cognitive jamming” measures thatcan disrupt this feedback loop. However, it should be noted that theblind despreading algorithms employed in one embodiment provideadditional protection against cognitive jamming measures even ifclosed-loop power control is used in the network, due the random andunpredictable selection of frequency channels, time slots, and evenintended receivers employed at the uplink transmitter, and due to theability for the despreading algorithms to adaptively excise CPDS signalsreceived at the uplink and downlink receivers, even if those signals arereceived at a much higher signal-to-noise ratio (SNR) than the signalsintended for the receiver.

In the downlink transmitter shown in FIG. 9, information intended fortransmission in each downlink slot of each frame (in accordance withFIG. 6) is passed through baseband encoding algorithms (20) to createbaseband source symbol stream b_(A)(n_(sym)); spread using thecyclic-prefix direct-sequence (CPDS) spreading processor (21) shown inFIG. 11 (described in detail below) to generate spread source datastream s_(S)(n_(chp)); pulse-amplitude modulated using araised-root-cosine (RRC) interpolation pulse (22); converted (23) to ananalog signal-in-space (SiS); upconverted (29) to desired sourcefrequency f_(S)(n_(slot)) selected by the downlink transmitter over timeslot; and transmitted over time slot n_(slot) at a source power levelP_(S) (30) that is held constant over every time slot.

Thus the method is: first passing said information through basebandencoding (20) to create a baseband source symbol stream b_(S)(n_(sym));then passing the baseband source symbol stream b_(S)(n_(sym)) to acyclic-prefix direct-sequence (‘CPDS’) spreader (21) which modulate eachdata segment to generate the spread source data stream s_(S)(n_(chp))output from the CPDS spreader (21) at each chip index n_(chp); thensubsequently pulse-amplitude modulating the spread source data streams_(S)(n_(chp)) output by a raised-root-cosine (‘RRC’) interpolationpulse (22);

converting (23) this result to an analog signal-in-space (‘SiS’);upconverting (29) this analog SiS to a desired source frequencyf_(S)(n_(slot)) selected by the downlink transmitter over time slotn_(slot); and transmitting this analog SiS over the desired sourcefrequency f_(S)(n_(slot)) over time slot n_(slot) at a source powerlevel P_(S) (30) that is held constant over every time slot.

Preferentially, in one embodiment, each downlink transmitter issynchronized to a common network time-standard, e.g., usingsynchronization information provided over separate infrastructure, or aGPS time-transfer device. This synchronization should be precise enoughto minimize DAP-to-DAP interference, but does not need to be precise toa fraction of a chip period.

Preferentially, in one embodiment, the frequency channelk_(chan)(n_(slot)) used to set source frequency f_(S)(n_(slot)) isgenerated using a pseudorandom selection algorithm based on the slotindex n_(slot) and the source index l_(S). In other words, the method isselecting a desired source frequency f_(S)(n_(slot)) to be used by thedownlink transmitter over time slot n_(slot) by selecting a frequencychannel k_(chan)(n_(slot)) using a pseudorandom selection algorithmbased on the slot index n_(slot) and the source index l_(S). In oneembodiment, f_(S)(n_(slot)) is known to each downlink receiver allowedto communicate with that transmitter, over at least a subset of slotswithin each frame. However, in alternate embodiments the downlinkreceiver may detect the transmit frequency over each slot or a subset ofmonitored slots and frequency channels, without coordination with thedownlink transmitter. Preferentially, in one embodiment, the sourcefrequency employed by each downlink transmitter is not coordinated withother downlink transmitters in the network; however, in alternateembodiments (employed outside the 902-928 MHz ISM band, which requiresuncoordinated hopping between network elements) the downlinktransmitters may use the same source frequency in each slot, e.g., tominimize intrusion on out-of-network users of the same frequency band,or may use disjoint source frequencies, e.g., to minimizeadjacent-network interference.

In the CPDS uplink spreading structure (21) shown in FIG. 10, theM_(sym) baseband source symbols intended for transmission overtime-frame n_(frame) are first passed to a 1:M_(sym) serial-to-parallel(S/P) convertor (63) to form M_(sym)×1 source symbol vector

b_(S)(n_(frame)) = [b_(S)(n_(frame)M_(sym) + n_(sym))]_(n_(sym) = 0)^(M_(sym) − 1).A unique M_(sym)×1 symbol mask vector

m_(RS)(n_(frame)) = [m_(RS)(n_(sym); n_(frame))]_(n_(sym) = 0)^(M_(sym) − 1)that is randomly varied from frame to frame is then inserted onto thedata (64) (procedure shown in FIG. 12), to provide physical security tothe source symbol stream, randomize the source data stream, and allowthe intended uplink receiver to differentiate the transmitted signalfrom other noise, co-channel interference, and in-network signalsimpinging on that receiver. The symbol mask vector is constructed fromthe element-wise multiplication (62) of an M_(sym)×1 source symbol maskvector m_(S)(n_(frame)) (that is unique to the uplink transmitter andrandomly varied between time frames), with an M_(sym)×1 receive symbolmask vector m_(R)(n_(frame);k_(dwell)(n_(frame))) (that is randomlyvaried between time frames and physical dwells and uses a receive symbolmask that is known to the intended receiver and common to every signalattempting to link with that receiver). This operation is depicted inFIG. 10 by the Schur productm_(RS)(n_(frame))=m_(R)(n_(frame),k_(dwell)(n_(frame)))∘m_(S)(n_(frame)).

In one embodiment, m_(S)(n_(frame)) is either:

-   -   known to the receiver, e.g., established during initial and/or        periodic network provisioning operations; or    -   a member of a set of sequences that is known to the receiver,        e.g., a Zadoff-Chu code with unknown index and/or offset; or    -   unknown to the receiver but estimable as part of the receive        adaptation procedure.

An important member of the last category of source symbol masks is thecomplex sinusoid given bym _(S)(n _(sym) ;n _(frame))=exp{j2πα_(S)(n _(frame))n _(sym)},  (Eq2)where α_(S)(n_(frame)) is a cyclic source frequency offset chosenrandomly or pseudorandomly over frame n_(frame). The cyclic sourcefrequency may be communicated to the receiver, or predictable via sideinformation provided at the time of installation of the SM or DAP,providing an additional means for validating the link.

In one embodiment, the source and receive symbol masks each possess aconstant modulus, i.e., |m_((•))(n_(sym))|≡1, to facilitate removal ofthe symbol mask at the receiver. In addition, except for the complexsinusoidal source symbol mask given in (Eq2), the source and receivesymbol masks are preferentially designed to be circularly symmetric,such that the masks have no identifiable conjugate self-coherencefeatures (

m_((•)) ²(n)e^(−j2παn)

≡0), where the angled brackets indicate averaging over index n, andcross-scrambling, such that the cross-multiplication of any two symbolmasks results in a composite symbol mask that appears to be a zero-meanrandom sequence to an outside observer.

In one embodiment, the receive symbol mask is a function of both thetime frame index n_(frame), and the physical dwell index k_(dwell), isgenerated using a pseudorandom selection algorithm based on bothparameters. In addition, the receive symbol mask can be made unique toeach uplink receiver in the network, in which case the receivers can usethat mask to identify only those uplink transmitters intending tocommunicate with that receiver; or it can be made common to everyreceiver in the network, allowing any receiver to despread any SM in itsfield of view. The latter property can be especially useful for networkaccess purposes (e.g., using a special receive mask intended just fortransmitter association and authentication purposes), and inmacrodiverse networks where symbol streams received and/or despread atmultiple uplink receivers are further aggregated and processed at highertiers in the network.

After insertion of the symbol mask (64), and if observed multipath timedispersion encountered by the channel is a substantive fraction of asingle symbol period, a cyclic symbol prefix is then inserted (65) intothe M_(sym)×1 masked symbol vector d_(S)(n_(frame)) , such thatd_(S)(n_(frame)) is replaced by N_(sym)×1 data vector

$\begin{matrix}{\left. {d_{S}\left( n_{frame} \right)}\leftarrow\left\lceil {d_{S}\left( {{\left( {n_{sym} - K_{sym}} \right){mod}\; M_{sym}};n_{frame}} \right)} \right\rbrack_{n_{sym} = 0}^{N_{sym} - 1} \right.,} & \left( {{Eq}\mspace{14mu} 3} \right)\end{matrix}$where M_(sym), K_(sym) and N_(sym)=M_(sym)+K_(sym) are the number ofencoded symbols, cyclic prefix symbols, and full data symbolstransmitted over the frame, respectively, and mod indicates modulo. Thecyclic symbol prefix protects against multipath dispersion with groupdelay T_(group)≤K_(sym)T_(sym) observed at the uplink receiver, whereT_(sym)=1/f_(sym) and f_(sym) are the symbol period and symbol rate forthe baseband symbol stream, respectively.

After insertion of the symbol mask (64) and (optional) symbol-levelcyclic prefix (65), the full N_(sym)×1 data vector d_(S)(n_(frame)) isspread by N_(chp)×1 source spreading code vector c_(S)(n_(frame)),chosen randomly or pseudorandomly over every time frame and not known atthe intended receiver. The source spreading code vector also has anoptional K_(chp)-chip cyclic chip prefix inserted into it (67), suchthat c_(S)(n_(frame)) is given by

$\begin{matrix}{{{c_{S}\left( n_{frame} \right)} = \left\lbrack {c_{S}\left( {{\left( {n_{chp} - K_{chp}} \right){mod}\; M_{chp}},n_{frame}} \right)} \right\rbrack_{n_{chp} = 0}^{N_{chp} - 1}},} & \left( {{Eq}\mspace{14mu} 4} \right)\end{matrix}$where

{c_(S)(n_(chp), n_(frame))}_(n_(chp) = 0)^(M_(chp) − 1)is an M_(chp)-chip base code used for frame n_(frame) andN_(chp)=M_(chp)+K_(chp). The cyclic chip prefix protects againstmultipath time dispersion with group delay T_(group)≤K_(chp)T_(chp)observed at the uplink receiver, where T_(chp)=1/f_(chp) and f_(chp) arethe chip period and chip rate for the baseband symbol stream,respectively.

Preferentially, if the observed multipath time dispersion is a smallfraction of a source symbol period, a cyclic chip prefix is insertedinto the spreading code and the cyclic symbol prefix is not implemented(K_(sym)=0); or, if the multipath time dispersion is larger than a smallfraction of a source symbol period, a cyclic symbol prefix is insertedinto the masked data vector and the cyclic chip prefix length is notimplemented (K_(chp)=0). In one embodiment, and for the long-range M2Mnetwork depicted in FIG. 5 and the 902-928 MHz deployment band andtime-frequency framing shown in FIG. 6, a nonzero cyclic chip prefix isinserted into the spreading code and the cyclic symbol prefix isdisabled. However, addition of both cyclic prefixes is not precluded bythe embodiments in the present description and, in one embodiment, maybe advantageous in some applications, e.g., mesh networks wheretransmitters may be communicating to a nearby receiver over one subsetof physical dwells in one frame, and to a remote receiver over a secondsubset of physical dwells in another frame.

In one embodiment, a modulation-on-symbol direct-sequence spreadspectrum (MOS-DSSS) method, in which the spreading code is repeated overevery baseband symbol within each hop, is used to spread the sourcesymbol vector d_(S)(n_(frame)) using the spreading codec_(S)(n_(frame)). Mathematically, the spreading operation (68) can beexpressed as a matrix outer-product operation given byS _(S)(n _(frame))=c _(S)(n _(frame))d _(S) ^(T)(n _(frame)),  (Eq5)in which c_(S)(n_(frame)) and d_(S)(n_(frame)) are the “inner” and“outer” components of the spreading process, respectively, followed by amatrix-to-serial or “matrix flattening” operation (69) to convert theN_(chp)×N_(sym) data matrix S_(S)(n_(frame)) resulting from thisoperation to a (N_(chp)N_(sym))-chip scalar data stream s_(S)(n_(chp))(70), in which each column of S_(S)(n_(frame)) is serially converted toa scalar data stream, moving from left to right across the matrix. Analternative, but entirely equivalent, representation can be obtainedusing the Kronecker product operations _(S)(n _(frame))=d _(S)(n _(frame))⊗c _(S)(n _(frame)),  (Eq6)to generate (N_(chp)N_(sym))×1 data vector s_(S)(n_(frame)), followed bya conventional (N_(chp)N_(sym)):1 parallel-to-serial (P/S) conversion(69) to s_(S)(n_(chp)) (70). The symbol stream may be real or complex,depending on the baseband source stream, and on the specific spreadingcode and symbol mask employed by the CPDS spreader.

The CPDS downlink spreading operations (21) shown in FIG. 11 areidentical to the CPDS uplink spreading operations shown in FIG. 10,except that data are transmitted every slot rather than every frame, andthe symbol mask and source spreading code are also generated every slotrather than every frame. In addition, the specific modulation parametersused at the uplink and downlink spreaders are different, based on thegroup delay and interference density observed by the uplink and downlinkreceivers. In particular, the uplink receivers are expected to observe alarge number of uplink emitters on each time slot and frequency channel,whereas the downlink receivers are expected to observe a small number ofdownlink emitters—typically one-to-two if source frequencies are notcoordinated between those emitters. In addition, in one embodiment theuplink transmitters advance their transmit timing to minimize groupdelay at the uplink receivers in the network, whereas the downlinktransmitters are synchronized to emit over coordinated transmissiontimes to minimize overlap between downlink-to-uplink interferencebetween widely-separated (but still visible) downlink transmitters inthe network.

As shown in FIG. 12, the symbol mask is preferentially applied, in oneembodiment, directly to the M_(sym)×1 source symbol vector b_(S), i.e.,in the ‘time domain,’ (72) if a cyclic symbol prefix is not applied atthe transmitter (K_(sym)=0), or is applied to the M_(sym)×1 discreteFourier transform (DFT) (73) of the source symbol vector B_(S), i.e., inthe ‘frequency domain,’ (74) if a cyclic symbol prefix is applied at thetransmitter (K_(sym)>0). In both cases, the mask is applied to theappropriate symbol vector using an element-wise multiply or Schurproduct operation. If the mask is applied in the frequency domain (74),the resultant masked symbol vector is then converted back to the timedomain using an inverse DFT (IDFT) operation (75). The DFT (73) and IDFT(75) operations can be implemented in a number of ways, including fastFourier transform (FFT) and inverse-FFT (IFFT) methods that minimizecomplexity of the overall masking operation. In addition, in someapplications, the baseband source vector may be generated directly inthe frequency domain and the initial DFT operation (73) can be dispensedwith, resulting in an effective OFDM modulation after the IDFT andcyclic symbol prefix operations are applied to the masked source vector.

Table 1 lists the exemplary uplink (UL) and downlink (DL) parametervalues used for deployment of this structure in the 902-928 MHz ISM bandusing one embodiment, which are further illustrated in FIG. 13 for theCPDS uplink, and FIG. 14 for the CPDS downlink. These parameters reflectthe different transmission characteristics between the uplink anddownlink time slots, as well as constraints imposed by transmissionwithin the 902-928 MHz ISM band.

TABLE 1 Exemplary Uplink and Downlink CPDS PHY, Transceiver ParametersParameter UL Value DL Value Comments PHY symbols/slot (M_(sym)) 480symbols 384 symbols Cyclic symbol prefix length (K_(sym))  0 symbols  3symbols Symbol-level cyclic prefix Full baseband symbols/slot (N_(sym))480 symbols 387 symbols PHY baseband symbol rate (f_(sym)) 16 symbol/ms40 symbol/ms Rate over Tx interval Active link duration 30 ms 9.675 msGuard time, end of link slot 75 μs 250 μs 40 ms hop dwell time Spreadingcode base length (M_(chp)) 16 chips 8 chips Cyclic chip prefix length(K_(chp))  4 chips 0 chips Chip-level cyclic prefix Full spreading codelength (N_(chp)) 20 chips 8 chips Spread chip rate 320 chip/ms 320chip/ms ~3.125 μs chip period Composite cyclic prefix duration 12.5 μs75 μs Max multipath dispersion Equivalent range (4/3 Earth) 3.75 km 22.5km UL timing advance needed RRC rolloff factor 25% 25% 320 kHz HPBW, 400kHz full BW Allowed FOA uncertainty ±50 kHz ±50 kHz >50 ppm LO offset,902- 928 MHz band Frequency channel bandwidth 500 kHz 500 kHz Compliant,FCC §15.247, ¶ (a)(1)(ii) Number hop channels 50 channels 50 channelsCompliant, FCC §15.247, ¶ (a)(1)(ii) Full hop bandwidth 25 MHz 25 MHzNumber transmit hops/node 1 1 Compliant, FCC §15.247, ¶ (a)(1)(i) Numberreceive hops/node 50 hop ≥1 hop DAP's receive all UL hops TDD slots perframe 100 slots 100 slots 4 second frame length Slot Tx per node eachframe 1 100  DL Tx every slot Hop rate each slot direction 0.25 hps 25hps Average time occupancy over 6 ms/SM 0.2 ms/DAP Compliant, FCC§15.247, ¶ 10 s (a)(1)(i) Max Tx conducted power into ANT 30 dBm (1 W)30 dBm (1 W) Compliant, FCC §15.247, ¶ (b)(2) Number Tx ANT's 1 ANT 1ANT SISO links assumed Tx ANT max directivity 6 dBi 6 dBi Compliant, FCC§15.247, ¶ (4 W EIRP) (4 W EIRP) (b)(4).

FIG. 15 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element that provides a truly randomkernel input from a sourcing sensor (76) using real-world chance eventsfrom which the source spreading code is generated randomly over everytransmit opportunity n_(dwell) (every frame on the uplink, and everytime slot on the downlink) in a randomizer element and then provided tothe CPDS spreader (21). This is one means whereby the embodiments in thepresent description can provide physical, or ‘reality-based’ securityrather than algorithmic or model-based security to the M2M network,which cannot be predicted by any intruder attempting to intercept and/orspoof transmission in that network. Moreover, because this sourcespreading code is generated without any provisioning from the network,this network element eliminates transference of network information(e.g., secure keys used to generate unique spreading codes) that can beintercepted, exploited, and subverted by intruder devices; eliminatesnetwork downloading required to transport such information; andeliminates need to manage dissemination of that information at highertiers in the M2M network.

FIG. 16 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element that provides a truly randomkernel input from a sourcing sensor (76) using real-world chance eventsfrom which the physical dwell index (time slot and frequency channel) isgenerated randomly over every time frame in a randomizer element andthen provided to the CPDS uplink transmitter. This is a second meanswhereby the embodiments in the present description can provide physical,or ‘reality-based’ security rather than algorithmic, model-based, orsecurity to the M2M network, which cannot be predicted by any intruderattempting to intercept and/or spoof uplink transmissions in thatnetwork. Because the uplink dwell index is generated without anyprovisioning from the network, this network element again eliminatestransference of network information that can be intercepted, exploited,and subverted by intruder devices; eliminates network downloadingrequired to transport such information; and eliminates the need tomanage dissemination of that information at higher tiers in the M2Mnetwork. Moreover, because the uplink receiver can unambiguouslydetermine the physical dwell employed in each uplink transmission, ifthe dwell-generating random seed element is combined with elementsdeterministically tied to the transmitter, e.g., trusted encryption keysknown only to the M2M network, this network element can be used tofurther increase the likelihood of detecting network intruders that lackaccess to that trusted information.

FIG. 17 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element that provides a truly randomkernel input from a sourcing sensor (76) using real-world chance eventsfrom which elements of the source symbol mask, e.g., a cyclic sourcefrequency offset, are generated randomly over every time frame in arandomizer element and then provided to the CPDS uplink spreader (21).This is a third means whereby the embodiments in the present descriptioncan provide physical, or ‘reality-based’ security rather thanalgorithmic or model-based security to the M2M network, which cannot bepredicted by any intruder attempting to intercept and/or spoof uplinktransmissions in that network. Moreover, because those symbol maskelements are generated without any provisioning from the network, thisnetwork element again eliminates transference of network informationthat can be intercepted, exploited, and subverted by intruder devices;eliminates network downloading required to transport such information;and eliminates need to manage dissemination of that information athigher tiers in the M2M network.

FIG. 18 shows a CPDS-enabled network element with a real-world,random-number, sourcing-sensor element that provides a truly randomkernel input from a sourcing sensor (76) using real-world chance eventsfrom which the intended uplink receiver is selected randomly from a setof candidate uplink receivers over every time frame in a randomizerelement and then provided to the CPDS uplink spreader (21). This is afourth means whereby the embodiments in the present description canprovide physical, or ‘reality-based’ security rather than algorithmic ormodel-based security to the M2M network, which cannot be predicted byany intruder attempting to intercept and/or spoof uplink transmissionsin that network. In addition, if a unique pseudorandom receive symbolmask is used at each uplink receiver in the network, this providesmultiple additional means whereby the embodiments in the presentdescription can provide physical security to the M2M network, byproviding an additional unpredictable search dimension to any algorithman intruder might use to “crack” the pseudorandom receive symbol mask;and, if the receive symbol masks have been compromised, by increasingthe number of unpredictable symbol masks that the intruder must employto intercept any uplink transmission. Lastly, because the network canunambiguously determine the intended receiver (49) in the network, ifthe receiver-generating random seed element (77) is combined withelements deterministically tied to the transmitter, e.g., trustedencryption keys known only to the M2M network, this network element canbe used to further increase the likelihood of detecting networkintruders that lack access to that trusted information.

As shown in FIG. 19, et the CPDS uplink receiver used in the long-rangeM2M network embodiment, the incoming received signal-in-space {tildeover (x)}_(R)(t) is coupled into the receiver antenna(e), amplified (90)and down-converted (91) from the analog incoming waveforms, digitizedusing analog-to-digital conversion (ADC) devices (93), and demultiplexed(DMX'd) (96) into physical dwells, i.e., separated into individual timeslots and frequency channels accessible to the receiver, using digitalsignal processing methods and hardware. These operations result indemultiplexer output signal sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1),where receive spreading factor N_(smp) is the number of time samples persource symbol period at the demultiplexer output sampling rate. Notethat this sampling rate can be substantively different than the chiprate employed at the transmitter; for example, if the transmitter chiprate is 320 chips/ms and the demultiplexer output rate is 400samples/ms, then the source spreading factor employed at the transmitterN_(chp)=16, but the receive spreading factor is N_(smp)=20. Similarly ifthe cyclic chip prefix employed at the transmitter is K_(chp)=4,encompassing a 12.5 μs time duration, then the cyclic chip prefixcovering the same time duration at the receiver is K_(smp)=5.

Each demultiplexed physical dwell of interest to the receiver is thenpassed through an uplink CPDS despreader (97) (shown in FIG. 21),modified with a feedback loop through an adaptation algorithm (98),which detects and estimates the frequency offset observed by thereceiving machine (including a cyclic source frequency offset if that isapplied at the uplink transmitter(s)) all sources intended for thereceiver; despreads and substantively separates those signals from eachother, creating symbol streams with relatively highsignal-to-interference-and-noise ratio (SINR) relative to the incomingsignal streams, except for gain, phase and frequency offset stillpresent on those symbol streams; and substantively excises signals notintended for the receiver. The resultant substantively separated symbolstreams are then fed through to a symbol demodulator (99) thatsubstantively removes the residual gain, phase and frequency offset(using frequency offset estimates also provided by the adaptationalgorithm), and removes additional environmental delay/degradationeffects actually observed by the receiving machine.

As shown in FIG. 20, the reception operations performed at the CPDSdownlink receiver in one embodiment are substantively similar to theCPDS uplink reception operations shown in FIG. 19, except that the dwellDMX operation, used at the uplink receiver to detect and despread largenumbers of incoming uplink transmissions, is replaced by afrequency-hopping receiver that demodulates the specific narrowbandfrequency channel containing the downlink transmission of interest tothe receiver over at least a subset of time slots, and which is known tothe downlink receiver over those time slots. Alternately, depending ontime-criticality of information incoming from the downlinktransmitter(s), the downlink receiver can randomly ‘scan’ over eachfrequency channel, or ‘camp’ on a particular frequency channel or subsetof channels with known favorable pathloss, and simply detect, despread,and demodulate transmissions as they arrive on that channel. Thisalternate approach is particularly well suited for applications orservices where an SM does not require acknowledgement of itstransmissions, e.g., data transport under User Datagram Protocol (UDP),and is particularly well enabled by the low level of networkprovisioning required by the embodiments in the present description.

As shown in FIG. 21, if the symbol mask is applied to the basebandsource data in the time domain as shown in the upper mask insertion pathin FIG. 12, demultiplexed dwell k_(dwell) is despread over time framen_(frame) by the sequential steps of:

-   -   Organizing the demultiplexer output signal sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1)into N_(smp)×N_(sym) matrix X_(R)(n_(frame),k_(dwell)) (110), whereN_(sym) is the number of transmitted symbols in the dwell, and removingthe cyclic chip prefix and (if applied at the transmitter) the cyclicsymbol prefix from that matrix (111), given in aggregate by

$\begin{matrix}{X = \begin{pmatrix}{x\left( {{N_{smp}K_{sym}} + K_{sym}} \right)} & \ldots & {x\left( {{N_{smp}\left( {N_{smp} - 1} \right)} + K_{smp}} \right)} \\\vdots & \ddots & \vdots \\{x\left( {{N_{smp}K_{sym}} + N_{smp} - 1} \right)} & \ldots & {x\left( {{N_{smp}\left( {N_{sym} - 1} \right)} + N_{smp} - 1} \right)}\end{pmatrix}} & \left( {{Eq}\mspace{14mu} 7} \right)\end{matrix}$for general received data sequence

{x(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(sym) − 1).

-   -   Removing the receive symbol mask from        X_(R)(n_(frame),k_(dwell)), using algorithm        X _(R)(n _(frame) ,k _(dwell))←X _(R)(n _(frame) ,k        _(dwell))diag{m* _(R)(n _(frame) ,k _(dwell))}  (Eq8)    -   where m_(R)(n_(frame),k_(dwell)) is the M_(sym)×1 receive symbol        mask vector over dwell k_(dwell) and time frame n_(frame), and        where diag{•} is the vector-to-diagonal matrix conversion        operation and (•)* is the complex conjugation operation.    -   Computing L_(port)×M_(sym) despread symbol matrix {circumflex        over (D)}_(R)(n_(frame),k_(dwell)) (113), using linear signal        separation algorithm        {circumflex over (D)} _(R)(n _(frame) ,k _(dwell))=W _(R)(n        _(frame) ,k _(dwell))X _(R)(n _(frame) ,k _(dwell)),  (Eq9)    -   where W_(R)(n_(frame),k_(dwell)) is an L_(port)×M_(smp) linear        combining matrix, computed as part of the adaptation procedure        shown in FIG. 23.    -   Converting the despread symbol matrix {circumflex over        (D)}_(R)(n_(frame), k_(dwell)) back to a sequence of L_(port)×1        despread symbol vectors

{d̂_(R)(n_(sym); n_(frame), k_(dwell))}_(n_(sym) = 0)^(M_(sym) − 1)by applying an M_(sym):1 parallel-to-serial (P/S) conversion operationto each column of {circumflex over (D)}_(R)(n_(frame),k_(dwell)) (114).

The despreading operations performed in the downlink CPDS despreader(97), shown in FIG. 22, are substantively equivalent to those shown inFIG. 21, except that they are only applied to time slots and frequencychannels monitored by the downlink receiver.

As shown in FIG. 23, in one embodiment, each dwell of interest to areceiver is then despread in accordance with the uplink despreaderstructure shown in FIG. 21 at the uplink receiver, and in accordancewith the downlink despreader structure shown in FIG. 22 at the downlinkreceiver. This comprises the following steps and substeps:

-   -   1^(st): Detect all sources intended for the receiver, estimate        key parameters of those signals, and develop linear combining        weights that can substantively despread the source symbols, by:        -   1.A computing the QR decomposition (QRD) of the            M_(smp)×M_(sym) received signal X_(R), resulting after            removal of cyclic prefix(es) (111) and the receive symbol            mask (112);        -   1.B generating an SINR/carrier revealing feature spectrum            that can (i) estimate the maximum attainable despread            signal-to-interference-and-noise ratio (‘maximum despreader            SINR’) of each signal impinging on the receiver that is            employing the receive symbol mask (‘authorized signals’),            given the received spreading code (source spreading code,            modulated by the transmission channel) of each signal and            interference impinging on the receiver at the dwell and            time-frame being monitored by the receiver, (ii) as a            function of observed frequency offset of that signal,            and (iii) provide statistics that can be used to develop            linear combining weights that can substantively achieve that            max-SINR, without knowledge of the received spreading code            for any of those signals, and without knowledge of the            background noise and interference environment;        -   1.C detecting L_(port) significant peak(s), in the            SINR/carrier revealing feature spectrum, and determining the            maximum despreader SINR and frequency offset of each peak;        -   1.D refining strengths (estimated maximum despreader SINR)            and locations (estimated frequency offsets) of each            significant peak, e.g., using Newton search methods; and        -   1.E developing L_(port)×M_(smp) linear combiner weight            matrices W_(R) that can substantively achieve the maximum            despreader SINR for each authorized signal, without            knowledge of the received spreading code for any of those            signals, and without knowledge of the background noise and            interference environment.    -   Then:    -   2^(nd): Despread and demodulate the detected sources:        -   2.A Despread detected source symbols—separate authorized            signals employing the receive symbol mask, and automatically            excise unauthorized signals not employing that mask;        -   2.B Substantively remove frequency offset from the despread            symbols, using the frequency offset estimates;        -   2.C Estimate and correct phase offsets, and further refine            frequency offsets to algorithm ambiguity using known            features of the source symbols, e.g., adherence to known            symbol constellations, unique words (UW's) and training            sequences embedded in the source symbols, known properties            of the source symbol mask, etc.;        -   2.D Remove algorithm ambiguity using additional features of            the source symbols, e.g., UW's, forward error correction            (FEC), cyclic redundancy check's (CRC's), etc.; and        -   2.E Decrypt traffic and protected medium access control            (MAC) data.    -   Then:    -   3rd: Perform ancillary processing as needed/appropriate:        -   3.A Compute received incident power (RIP) for open-loop            power control, using SINR and channel estimates provided by            the CPDS despreading algorithm (uplink receiver);        -   3.B Correlate source internals, externals with trusted            information, using dwell, intended receiver and source            symbol mask elements provided by the CPDS receiver and            despreading algorithm; and        -   3.C Detect network intrusions—revise symbol masks if needed            (downlink receiver);

In one embodiment, specific partially or fully-blind adaptationalgorithms can meet the criteria described above include:

-   -   The FFT-enabled least-squares (FFT-LS) detection, carrier        estimation, and signal extraction algorithm, which can be        derived as a maximum-likelihood estimate of carrier frequency        for signals with known content but unknown carrier offset which        exploits known training signals inserted in the baseband symbol        sequence at every source (e.g., in “Unique Word” fields, or more        sophisticated embedded pilots) to determine the linear combining        weights. FFT-LS is most useful at high symbol rates (>3        bits/symbol), as the high dimensionality of the CPDS linear        combiner requires a large set-aside of non-information-bearing        symbols for training purposes (e.g., ≥40 UL symbols, e.g., 8% of        each slot, for the baseline uplink signal).    -   The auto-self-coherence-restoral (A-SCORE) algorithm is        described in, U.S. Pat. No. 7,079,480 entitled “Enhancing        Security and Efficiency of Wireless Communications through        Structural Embedding” by the present inventor. A-SCORE exploits        nonzero (by design, perfect) temporal correlation induced as        part of the embedded invariance algorithm. A-SCORE is most        useful at moderate symbol rates (<3 bits/symbol), and over data        bursts that are too short to allow set-aside for long training        sequences (e.g., greater than 30% of the source symbols at 3        bits/symbol, or greater than 20% of the source symbols at 1        bit/symbol).    -   The conjugate self-coherence restoral (C-SCORE) algorithm, which        exploits nonzero conjugate self-coherence of the baseband symbol        sequence, if it exists prior to application of the masking        signal, and which estimates the twice-carrier rate of that        signal (including any cyclic source frequency offset applied to        the source symbol mask). C-SCORE is most useful for symbol        streams with perfect conjugate self-coherence, e.g., binary        phase-shift keyed (BPSK) and amplitude-shift keyed (ASK) symbol        sequences.

All of these algorithms are blind despreading methods that do notrequire knowledge of the spreading code to adapt the despreader.Moreover, except for incorporation of structure to resolve knownambiguities in the despreader output solutions, C-SCORE and A-SCORE arefully-blind despreading methods that require no knowledge of the sourcesymbol sequence, and use the entire symbol stream to adapt thedespreader. All of these methods also asymptotically converge to themax-SINR solution over data bursts with high usable time-bandwidthproduct (M_(sym)/M_(smp) large, where M_(sym) is the number of symbolsused for training purposes). Moreover, all of the receiver adaptationalgorithms are assumed to operate on a slot-by-slot basis, such thatdespreader weights for each slot are computed using only data receivedwithin that slot. Lastly, all of these methods yield an SINR-likefeature spectrum which can be used to detect and estimate the carrieroffset of the symbol sequences to within a Nyquist zone ambiguity, i.e.,carrier modulo symbol rate for FFT-LS and A-SCORE, and twice-carriermodulo symbol rate for C-SCORE.

In one embodiment, the baseband source sequence is BPSK and thereforepossesses a perfect conjugate self-coherence at its twice-frequencyoffset. Moreover, if the symbol masks applied at the spreader arecircularly symmetric, the received symbol streams have no identifiableconjugate self-coherence prior to the symbol demasking operation. Afterthe demasking operation, the symbols employing that mask, and only thesymbols employing that mask, are converted to perfectly conjugateself-coherent signals that provide strong peaks at their twice-carrierfrequencies. As a consequence, the despreader is ideally suited foradaptation using a C-SCORE algorithm.

The full C-SCORE method is described as follows:

-   -   Compute the Q component Q_(R) of the QRD of X_(R) ^(T)        (corresponding to the transpose of the matrix X given in Eq. 7)        using a modified Gram-Schmidt orthogonalization (MGSO)        algorithm;    -   Compute {S_(R)(α_(k))} from Q_(R) at uniform trial frequencies

{α_(k)} = {2π k/K_(DFT)}_(k = 0)^(K_(DFT) − 1)using a fast Fourier transform (FFT) algorithm,

$\begin{matrix}{{\left\{ \left( {S_{R}\left( \alpha_{k} \right)} \right)_{m,m^{\prime}} \right\} = {{DFT}_{K_{FFT}}\left\{ {\left( {q_{R}(n)} \right)_{m}\left( {q_{R}(n)} \right)_{m^{\prime}}} \right\}}},\left\{ {\begin{matrix}{{m = 1},\ldots\mspace{14mu},M_{smp}} \\{{m^{\prime} = 1},\ldots\mspace{14mu},m}\end{matrix}.} \right.} & \left( {{Eq}\mspace{14mu} 10} \right)\end{matrix}$

To facilitate subsequent operations, compute and store the½M_(smp)(M_(smp)+1)M_(sym) unique cross-multiplications used in (Eq10)prior to the FFT operation. These cross-multiplications can also be usedto compute (Eq10) for other masks.

-   -   Initialize u₁(α_(k))=e_(M) _(smp) (M_(smp)), and estimate        {η₁(α_(k)),u₁(α_(k))} using power method recursion

$\begin{matrix}{\left. {u_{1}\left( \alpha_{k} \right)}\leftarrow{{S_{R}\left( \alpha_{k} \right)}{u_{1}\left( \alpha_{k} \right)}} \right.\left. {u_{1}\left( \alpha_{k} \right)}\leftarrow{{S_{R}^{H}\left( \alpha_{k} \right)}{u_{1}\left( \alpha_{k} \right)}} \right.{{\eta_{1}\left( \alpha_{k} \right)} = {{u_{1}\left( \alpha_{k} \right)}}_{2}}\left. {u_{1}\left( \alpha_{k} \right)}\leftarrow{{u_{1}\left( \alpha_{k} \right)}/{{\eta_{1}\left( \alpha_{k} \right)}.}} \right.} & \left( {{Eq}\mspace{14mu} 11} \right)\end{matrix}$

-   -   Select the L_(port) strongest peaks in {η₁(α_(k))},        L_(port)=M_(smp).    -   Estimate the dominant mode {η₁({circumflex over        (α)}),u₁({circumflex over (α)})} of S({circumflex over (α)}) at        each peak frequency {circumflex over (α)}, and optimize the        frequency location to sub-bin accuracy, using an alternating        projections method that alternately optimizes {η₁({circumflex        over (α)}),u₁({circumflex over (α)})} given fixed {circumflex        over (α)} using (Eq11), and optimizes {circumflex over (α)} to        maximize Re{u₁ ^(T)S_(R)(α)u₁} given fixed u₁ using a Newton        recursion. This processing step reuses the cross-multiplication        products computed in (Eq10).    -   Estimate the maximum attainable signal-to-interference-and-noise        ratio (SINR) of the despreader at peak {circumflex over (α)}        using {circumflex over (γ)}_(max)({circumflex over        (α)})=η₁({circumflex over (α)})/(1−η₁({circumflex over (α)}))        and thin the C-SCORE peaks if needed.    -   Compute the spatially whitened minimum mean-square error (MMSE)        weights using the formula

$\begin{matrix}{{{g\left( \hat{\alpha} \right)} = {\sqrt{{{\hat{\gamma}}_{{ma}\; x}\left( \hat{\alpha} \right)}\left( {1 + {{\hat{\gamma}}_{m\; a\; x}\left( \hat{\alpha} \right)}} \right)}e^{{- j}\;\frac{1}{2}\angle\;{u_{1}^{T}{(\hat{\alpha})}}{S{(\hat{\alpha})}}{u_{1}{(\hat{\alpha})}}}}}{{u_{R}\left( \hat{\alpha} \right)} = {{g\left( \hat{\alpha} \right)}{u_{1}\left( \hat{\alpha} \right)}}}} & \left( {{Eq}\mspace{14mu} 12} \right)\end{matrix}$

-   -   Despread the symbol stream using {circumflex over        (d)}_(R)({circumflex over (α)})=Q_(R)u_(R)({circumflex over        (α)}), and P/S convert to scalar stream {circumflex over        (d)}_(R)(n_(sym);{circumflex over (α)}).    -   Remove the carrier offset using {circumflex over        (d)}_(S)({circumflex over (α)})=Δ({circumflex over        (α)}){circumflex over (d)}_(R)({circumflex over (α)}), where

Δ(α̂) = diag(e^(−j 2π α̂n_(sym))}_(n_(sym) = 0)^(M_(sym) − 1).

-   -   Use additional source signal structure to resolve the ±(±1)^(n)        ^(sym) amplitude ambiguity inherent to the algorithm, e.g.,        using a Unique Word inserted into the symbol stream, and convert        {circumflex over (α)} to a true carrier offset (mod the symbol        rate).    -   Optionally refine the carrier, despreading weights, and source        symbol stream using decision-direction recursion

$\begin{matrix}{{{{\hat{d}}_{R}\left( \hat{\alpha} \right)} = {Q_{R}{u_{R}\left( \hat{\alpha} \right)}}}{{{{\hat{d}}_{S}\left( \hat{\alpha} \right)} = {{sgn}\left\{ {{Re}\left( {{\Delta\left( \hat{\alpha} \right)}{{\hat{d}}_{R}\left( \hat{\alpha} \right)}} \right\}} \right\}}},{{\Delta\left( \hat{\alpha} \right)} = {{diag}\left\{ e^{{- j}\; 2\;\pi\;\hat{\alpha}n_{sym}} \right\}_{n_{sym} = 0}^{M_{sym} - 1}}}}{{\hat{\alpha} = {\arg\mspace{14mu}{\max\limits_{\alpha}{{u_{R}\left( \hat{\alpha} \right)}}_{2}^{2}}}},{{u_{R}\left( \hat{\alpha} \right)} = {Q_{R}^{H}{\Delta^{*}\left( \hat{\alpha} \right)}{{\hat{d}}_{S}\left( \hat{\alpha} \right)}}},}} & \left( {{Eq}\mspace{14mu} 13} \right)\end{matrix}$where the carrier estimate and despreading weights are jointly updatedusing a Newton recursion.

The C-SCORE algorithm generates a single feature spectrum with multiplepeaks at twice the carrier (mod the symbol rate) of every sourcecommunicating with the receiver, and with peak strengths consistent withthe maximum attainable SINR of the despreader. Random cyclic complexsinusoids are also completely transparent to the C-SCORE algorithm, asthe complex sinusoid may simply shift the location of peaks in thefeature spectrum. This may improve resistance to collisions, byrandomizing the location of all of the peaks in the spectrum. This canalso provide additional resistance to spoofing if the cyclic offset usedby each source is partially or fully derived from information known onlyto the source and receiver.

If a cyclic symbol prefix is inserted into the baseband symbol vector atthe transmitter, and the operations shown on the lower branch of FIG. 12are used to insert the symbol mask at the transmitter, then thealternate ‘frequency domain’ despreading structure shown in FIG. 24 canbe employed to despread the received signal dwells. In this despreader,the input signal sequence

{x_(R)(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(sym))is first converted to a N_(smp)N_(sym)×1 vector using a 1:N_(smp)M_(sym)serial-to-parallel converter (115), and the first K_(sym) symbols(N_(smp)K_(sym) samples) encompassing the cyclic symbol prefix areremoved (116). The resulting N_(smp)M_(sym)×1 data vector is then passedthrough an N_(smp)M_(sym)-point DFT (117), reshaped into anN_(smp)×M_(sym) matrix, and transposed (118) to form M_(sym)×N_(smp)matrix

X_(R) = [X_(R)( : , k_(sym))]_(k_(sym) = 0)^(M_(sym) − 1),where k_(sym) is the index for each column of X_(R). The receive symbolmask (112) is then removed from X_(R) using (Eq8), and each column ofX_(R) is despread using linear combining algorithm (119){circumflex over (D)} _(R)(:,k _(sym))=W _(R)(k _(sym))X _(R)(:,k_(sym)),  (Eq14)where

{W_(R)(k_(sym))}_(k_(sym) = 0)^(M_(sym) − 1)  are  a  set  of  M_(sym)  L_(port) × M_(smp)linear combining matrices, computed as part of an adaptation procedure,and individually applied to each column of X_(R). Each row of theresultant L_(port)×M_(sym) despread data matrix {circumflex over(D)}_(R) is then converted back to the time domain using anM_(sym)-point inverse DFT (IDFT) operation (120), and converted to asequence of L_(port)×1 despread symbol vectors (114)

$\begin{matrix}{\left\{ {{\hat{d}}_{R}\left( n_{sym} \right)} \right\}_{n_{sym} = 0}^{M_{sym} - 1}.} & \;\end{matrix}$

It should be noted that any uplink transmitter employing the samereceive symbol mask can use that mask to detect and despread emissionsfrom neighboring uplink transmitters. As a consequence, information sentfrom these transmitters should possess additional encryption to protectthat information from eavesdropping by neighboring network members. Thiscan be accomplished at the physical layer, for example by adding a BPSKsource symbol mask to each uplink transmission that still allows uplinkdespreading using C-SCORE; or by adding stronger encryption at higherlayers in the OSI protocol stack; or by a combination of bothstrategies.

It should also be noted that this capability does not compromise abilityfor the network to defeat man-in-the-middle attacks, as the transmissionparameters of the uplink transmitters cannot be predicted. It does placeincreased importance on truly random choice of those parameters, as anintelligent adversary could eventually learn the keys underlyingpseudorandom choices if weak enough.

In fact, this capability can greatly enhance ability for the network todetect intruders, by allowing SM's to measure and transmit observablesof their neighbors to the network DAP's as a normal part of theiroperation. Any intruder attempting to spoof an SM would be instantlyidentified by virtue of observables of the correct SM reported to theDAP by its neighbors.

For example, an SM can simply pick an uplink dwell to listen on;intercept and demodulate any SM transmissions during that dwell; breakout a MAC header containing information sent some a portion of themessage known to contain the SM's Address (which might still beencrypted using keys possessed by only the DAP and SM itself), and sendthat information along with PHY observables of the intercepted SM, e.g.,the dwell index, source frequency offset, intercepted frame index, andintended receive DAP (if non-macrodiverse usage) back to a the networkin a later transmission. That information alone should be enough toeventually uncover any radio attempting to spoof transmission.

This capability can also greatly facilitate the implementation of meshnetworks to further improve reliability of the network, and reduceenergy emitted or dissipated by the uplink transmitters.

One embodiment seamlessly extends to additional transceiver and networkimprovements, including:

-   -   Use of spatial and polarization diverse antenna arrays at any        node in the network. In this case the spreading code can be        repeated or randomly extended over each antenna employed at the        transmitter, and the dimensionality of the despreading        algorithms is simply multiplied by the number antennas employed        at the receiver.    -   Macrodiverse uplink despreading methods in which part or all of        the despreading operations are performed at a higher tier of the        network.

Both of the above extensions can be implemented without any substantivechange to the transmission and spreading structures described herein,and do not require reciprocity of the uplink and downlink channels orcalibration techniques to enforce such reciprocity.

FIG. 25 shows a weakly-macrodiverse uplink despreading method, in whichthe DAP-specific receive symbol mask is replaced by a common ornetwork-wide receive symbol mask m_(R)(n_(frame),k_(dwell)), which isused by every SM attempting to transmit over physical dwell k_(dwell) intime frame n_(frame), and which is assumed to evolve in a pseudorandommanner known to the SM over every frame. Thus the method is using any ofthe set of common receive symbol mask for that set of DAPs and the setof common receive symbol masks for all DAPs in the network; using as theform for each said common receive symbol maskm_(R)(n_(frame),k_(dwell)); using this form by every SM attempting totransmit over physical dwell k_(dwell) in time frame n_(frame); evolvingthis form in a pseudorandom manner known to the SM over every frame; andthat on receiving and downconverting a symbol stream for any device,uses this form to despread the symbol stream and then passing the symbolstream then on to the respective receiving device.

In more complex systems and other embodiments, this network mask may bebroken into geographic-specific zonal masks, in order to differentiatebetween SM's based on their proximity to different clusters of DAP's.Because the symbol masks do not disrupt the MOS-DSSS structure of thesignals, they still allow signals outside that geographical region to beexcised by the despreader; however, only the signals within that regionmay be discovered and extracted by the despreader employed that symbolmask.

The CPDS method is particularly well suited to weakly-macrodiversecombining. The cyclic prefixes provide a high degree of tolerance totiming error between signals received at the DAP's in the network; infact, it is likely that no timing error may occur at SM's that can mostbenefit from macrodiverse processing, e.g., SM's that are atnearly-equal range to multiple DAP's, and are therefore received atnear-equal RIP at those DAP's. Moreover, because the SM uplink signalsare despread at the DAP's, the bulk of operations needed to despreadthose signals are distributed over the network, with a relatively smallnumber of operations needed at the network level. Lastly, thedespreading performed at the DAP's also compress data needed to betransferred to the central site—by a factor of 20 at least in oneembodiment, much more if the despread symbols are quantized to lowprecision before being uploading to the central site.

FIG. 26 shows an even more powerful strongly-macrodiverse extension, inone embodiment, in which the entire M_(smp)×M_(sym) demasked DAP datamatrices

{X_(R)(n_(frame), k_(dwell); l_(R))}_(l_(R) = 1)^(l_(R))are uploaded to a central processing site (125). In this system, thedata matrices are “stacked” into an L_(R)M_(smp)×M_(sym) network datamatrix X_(R)(n_(frame),k_(dwell)) (128) given by

$\begin{matrix}{{{X_{R}\left( {n_{frame},k_{dwell}} \right)} = \begin{pmatrix}{X_{R}\left( {n_{frame},{k_{dwell};1}} \right)} \\\vdots \\{X_{R}\left( {n_{frame},{k_{dwell};L_{R}}} \right)}\end{pmatrix}},} & \left( {{Eq}\mspace{14mu} 15} \right)\end{matrix}$

The network data matrix is then passed to a network-level despreader(97) that on receiving and downconverting a symbol stream for any deviceremoves the DAP carrier offsets

{α_(R)(l_(R))}_(l_(R) = 1)^(L_(R))(if needed); detects the sources {l_(S)}_(k′) _(dwell) _((l) _(S) _()=k)_(dwell) using that channel; estimates their carrier offsets{α_(S)(l_(S))}_(k′) _(dwell) _((l) _(S) _()=k) _(dwell) , develops a setof linear combiner weights with L_(R)M_(smp) degrees of freedom, anduses those combining weights to extract all of those SM's symbol streamsfrom the network data matrix, to be used by the network.

The macrodiverse extensions can improve the security, efficiency, andcomplexity of M2M networks, by exploiting the additional route diversityof macrocellular and mesh networks. Large scale network analyses haveestablished that weakly-macrodiverse networks can provide as much as 3dB of link margin in the long-range M2M use scenario shown in FIG. 5,and the strongly-macrodiverse network can provide much as 12 dB of linkmargin in the same scenario. This link margin can be traded againsttransmit power, link data rate, or network density to further improveperformance or security of the network. Moreover, both approachesprovide inherent resistance to denial-of-service attacks, as an attackerwould need to simultaneously attack every uplink receiver in the networkto prevent reception of information by a macrodiverse network. Inaddition, migrating the most computationally complex operations to acentral processing node can significantly reduce complexity of theuplink receivers in the network.

FIG. 27 shows an FCC § 15.247 compliant time-frequency framing structurefor an alternate Frame Synchronous (FS) system embodiment, and for thelong-range M2M cell shown in FIG. 5. The FS framing structure is similarto the CPDS framing structure shown in FIG. 6, except in this embodimentthe durations of the DL subslots are 9 ms, and the preceding andfollowing guard intervals are each 500 μs. These much higher guardintervals allows the alternate FS network to be used in applicationswhere the SM's and/or DAP's are communicating over much longer ranges orat much higher altitudes, e.g., in airborne or satellite communicationnetworks. In addition, this frame structure provides sufficient guardinterval to eliminate the need for SM timing advancement in manyapplications; or can be used to provide additional security to thenetwork, e.g., by adding pseudorandom jitter to the format.

FIG. 28 shows an uplink transmitter structure employing the alternate FSspreading strategy. The transmitter structure is substantively similarto the CPDS uplink transmitter structure shown in FIG. 7, except thatthe information intended for transmission is first passed through abaseband modulator (135) that generates a baseband data sequenced_(S)(n_(DAC)) with arbitrary modulation format, and with a sample rateequal to the interpolation rate of the transmitter digital-to-analogconvertor(s) (DAC(s)) (23). The baseband data sequence is then separatedinto segments of data intended for transmission over a singletime-frequency dwell within each frame, and passed to a framesynchronous (FS) spreader (136) that spreads it over time within anuplink dwell subslot, resulting in an FS spreader output signal sequences_(S)(n_(DAC)) that also has a sample rate equal to the interpolationrate of the transmitter DAC (23). The FS spreader output signal is thenconverted to analog format in the transmitter DAC(s) (23),frequency-shifted (29) to RF transmit frequency f_(S)(n_(frame)) (27),amplified (31) to transmit power level P_(S)(n_(frame)) (30), andtransmitted to its intended uplink receiver.

In one embodiment, a possible feature of the FS embodiment is itsability to be used with any baseband modulation format. The exemplary FSsystem described here uses a spectrally efficient OFDM modulation formatwith a cyclic prefix allowing much higher tolerance to observed groupdelay at the uplink receiver.

The algorithm used to compute the time-slot start time t_(S)(n_(frame))(24), frequency channel center frequency f_(S)(n_(frame)) (27), andtransmit power level P_(S)(n_(frame)) (30) in each time frame n_(frame)is computed using the operations shown in FIG. 8, and allows fullyrandomized selection of transmit dwell, k_(dwell)(n_(frame)) andintended uplink receiver l_(R)(n_(frame)). However, the large cyclicprefix can obviate the need for the timing advancement operation shownin that Figure, or can be used to further improve physical security ofthe network by pseudorandomly adjusting t_(S)(n_(frame)) (24) in eachtime frame, or by pseudorandomly adjusting the duration of each OFDMcyclic prefix before or during the FS spreading operation.

FIG. 29 shows a downlink transmitter structure employing the alternateFS spreading strategy. The transmitter structure is substantivelysimilar to the CPDS downlink transmitter structure shown in FIG. 9,except that the information intended for transmission is also firstpassed through a baseband modulator (135) that generates a time-slot ofbaseband data with arbitrary modulation format and sample rate at thepresumed interpolation rate of the transmitter DAC(s) (23), whereby itis further spread in time by the FS spreader (136), resulting in aspreader output signal with the same sampling rate. The FS spreaderoutput signal is then converted to analog format in the transmitterDAC(s) (23), frequency-shifted to RF transmit frequency f_(S)(n_(slot)),amplified (31) to (fixed) transmit power level P_(S) (30), andtransmitted to its intended downlink receiver. The frequency channelk_(chan)(n_(slot)) used to set center frequency f_(S)(n_(slot)) (47) ineach time slot is pseudorandomly adjusted based on the time slot indexn_(slot) and source index l_(S), and is assumed to be known ordetectable to intended downlink receivers in the network.

In the FS uplink spreading structure shown in FIG. 30, the N_(DAC)baseband source samples intended for transmission over time-framen_(frame) are first passed to a 1:N_(DAC) serial-to-parallel (S/P)convertor (143) to form N_(DAC)×1 source symbol vector

d_(S)(n_(frame)) = [d_(S)(n_(frame)N_(DAC) + n_(DAC))]_(n_(DAC) = 0)^(N_(DAC) − 1).The source symbol vector is then spread over time using an N_(chp)×1spreading code vector c_(RS)(n_(frame)) that is randomly orpseudorandomly generated in each time frame. Mathematically, thespreading operation (144) can be expressed as a matrix outer-productoperation given byS _(S)(n _(frame))=d _(S)(n _(frame))c _(RS) ^(T)(n _(frame))  (Eq16)in which d_(S)(n_(frame)) and c_(RS)(n_(frame)) are the “inner” and“outer” components of the spreading process, respectively, followed by amatrix-to-serial or “matrix flattening” operation (145) to convert theN_(DAC)×N_(chp) data matrix S_(S)(n_(frame)) resulting from thisoperation to a (N_(DAC)N_(chp))-chip scalar data stream s_(S)(n_(DAC)),in which each column of S_(S)(n_(frame)) is serially converted to ascalar data stream, moving from left to right across the matrix. Analternative, but entirely equivalent, representation can be obtainedusing the Kronecker product operations _(S)(n _(frame))=c _(RS)(n _(frame))⊗d _(S)(n _(frame))  (Eq17)to generate (N_(DAC)N_(chp))×1 data vector s_(S)(n_(frame)), followed bya conventional (N_(DAC)N_(chp)):1 parallel-to-serial (P/S) conversion tos_(S)(n_(DAC)). The symbol stream may be real or complex, depending onthe baseband source stream and the specific spreading code used by theFS spreader (136).

Comparing (Eq16)-(Eq17) with (Eq5)-(Eq6), the FS spreading operation isseen to be the reverse or ‘dual’ of the spreading operation performed inthe CPDS spreader. Alternately, the baseband data modulates the codesequence, that is, the baseband data in the FSS airlink takes on thesame function as the spreading code in the CPDS airlink, and vice versa.

In the absence of known and exploitable structure of the baseband sourcevector, the spreading code c_(RS)(n_(frame)) is constructed from theelement-wise multiplication (142) of an N_(chp)×1 source spreading codevector c_(S)(n_(frame)) that is unique to the uplink transmitter andrandomly varied between time frames, with an N_(chp)×1 receive spreadingvector c_(R)(n_(frame);k_(dwell)(n_(frame))) that is randomly variedbetween time frames and physical dwells. This operation is depicted inFIG. 30 by the Schur productc_(RS)(n_(frame))=c_(R)(n_(frame),k_(dwell)(n_(frame)))∘c_(S)(n_(frame)).

In other embodiments, in the absence of known and exploitable structureof the baseband source vector, c_(S)(n_(frame)) is further either:

-   -   known to the receiver, e.g., established during initial and/or        periodic network provisioning operations; or    -   a member of a set of sequences that is known to the receiver,        e.g., a Zadoff-Chu code with unknown index and/or offset; or    -   unknown to the receiver but estimable as part of the receive        adaptation procedure, e.g., a 1733 complex sinusoid given by

$\begin{matrix}{{{c_{S}\left( n_{frame} \right)} = \left\lbrack {\exp\left\{ {j\; 2\;\pi\;{\alpha_{S}\left( n_{frame} \right)}n_{chp}} \right\}} \right\rbrack_{n_{chp} = 0}^{N_{chp} - 1}},} & \left( {{Eq}\mspace{14mu} 18} \right)\end{matrix}$

-   -   where α_(S)(n_(frame)) is a cyclic source frequency offset        chosen randomly or pseudorandomly over frame n_(frame).

In the latter case, the cyclic source frequency offset may becommunicated to the receiver, or predictable via side informationprovided at the time of installation of the SM or DAP, providing anadditional means for validating the link. Except for the complexsinusoidal frequency offset, the source and receive code spreadingvectors are preferentially designed to be circularly symmetric, suchthat the spreading vectors have no identifiable conjugate self-coherencefeatures

⟨c_((•))²(n)e^( = −j 2 πα n)⟩ = 0),and cross-scrambling, such that the cross-multiplication of any twospreading vectors results in a composite spreading vector that appearsto be a zero-mean random sequence to an outside observer.

Note that the FS spreader does not insert a ‘symbol mask’ into thespreader input signal—the source spreading code takes on the samefunction as the receive symbol mask in the FS format. This sourcefrequency offset can also be generated using the symbol maskrandomization network element shown in FIG. 17. As in the CPDS spreader,the random cyclic frequency offset provides additional differentiationbetween co-channel signals, as well as an additional spoof detection ifthat offset is known, estimable, communicated to the uplink receiver viaother means.

If the baseband source signal contains additional known features, e.g.,structural embedding taught in U.S. Pat. No. 7,079,480 or embedded pilotsignals taught in U.S. Pat. No. 8,363,744, the entire spreading codevector c_(RS)(n_(frame)) can be randomly generated, e.g., using thespreading code randomization network element shown in FIG. 15. This canprovide additional differentiation between co-channel signals, as wellas an additional spoof detection if that offset is known, estimable,communicated to the uplink receiver via other means.

The FS downlink spreading operations shown in FIG. 31 are identical tothe FS uplink spreading operations shown in FIG. 30, except that dataare transmitted every slot rather than every frame, and the spreadingcode is also generated every slot rather than every frame. In addition,the specific spreading parameters used at the uplink and downlinkspreaders are different, based on the traffic requirements of the uplinkand downlink and the durations of the uplink and downlink slots. Thebaseband modulation formats can also be different in both linkdirections, or can be exactly the same in order to reduce complexity ofthe overall system.

Table 2 lists the exemplary uplink (UL) and downlink (DL) parametervalues used for deployment of this structure in the 902-928 MHz ISM bandusing one embodiment, which are further illustrated in FIG. 32 for theFS uplink and FIG. 33 for the FS downlink. These parameters reflect theconstraints imposed by transmission within the 902-928 MHz ISM band.

TABLE 2 Exemplary Uplink and Downlink FS PHY, Transceiver ParametersParameter UL Value DL Value Comments Subcarriers/symbol (N_(sym)) 480symbols 480 symbols Subcarrier separation 800 kHz 800 kHz 1.25 ms FFTduration Symbol cyclic prefix 250 μs 250 μs 1.5 ms OFDM symbol Equiv.range (4/3 Earth) 75 km 75 km Timing advance unneeded Spread code length(N_(chp)) 20 chips 6 chips Cyclic chip prefix unneeded Active linkduration 30 ms  9 ms Baseband symbol rate (f_(sym)) 16 symbol/ms 53.33symbol/ms Guard time, end of link slot 500 μs 500 μs OFDM bandwidth 384kHz 384 kHz Allowed FOA uncertainty ±50 kHz ±50 kHz >50 ppm LO offset,902- 928 MHz band Hop dwell bandwidth 500 kHz 500 kHz Compliant, FCC§15.247, ¶ (a)(1)(ii) Number hop channels 50 channels 50 channelsCompliant, FCC §15.247, ¶ (a)(1)(ii) Full hop bandwidth 25 MHz 25 MHzNumber transmit hops/node 1 hop Tx/SM 1 hop Tx/DAP Compliant, FCC§15.247, ¶ (a)(1)(i) Number receive hops/node 50 hop Rx/DAP 1 hop Rx/SMDAP's can receive all UL's TDD slots per frame 100 slots 100 slots 4second frame length Slot Tx/node each frame 1 100 DAP Tx every slot, SMTx once per frame Hop rate each slot direction 0.25 hps 25 hps Averagetime occupancy 6 ms/SM 0.2 ms/DAP Compliant, FCC §15.247, ¶ over 10 s(a)(1)(i) Max Tx conducted power 30 dBm (1 W) 30 dBm (1 W) Compliant,FCC §15.247, ¶ into ANT (b)(2) Number Tx ANT's 1 ANT 1 ANT SISO linksassumed Tx ANT max directivity 6 dBi (4 W EIRP) 6 dBi (4 W EIRP)Compliant, FCC §15.247, ¶ (b)(4)

The parameters shown in Table 2 are similar in many respects to thoseshown in Table 1 for the CPDS spreader, but also possess importantdifferences. In particular, the exemplary FS spreader employs an OFDMbaseband modulation format with the same number of subcarriers, cyclicprefix, subcarrier frequency spacing, and baseband information rate oneach side of the link, and the exemplary FS spreader does not requiretiming advancement at the uplink transmitters. This can reduce thecomplexity of the FS transceivers, as the substantively similarprocessing hardware and software can be used to implement the FStransmitter and receiver at both ends of the link, and allows the FStransceivers to be used in networks with extreme long range, e.g.,airborne and satellite communication networks.

The FS uplink receiver shown in FIG. 34 is substantively similar to theCPDS uplink receiver shown in FIG. 19, except that each received dwellis despread in an FS despreader (147) rather than a CPDS despreader(97), resulting in L_(port)×1 vector FS despreader output signalsequences

{y_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp) − 1),comprising the L_(port) signals that are intended for the uplinkreceiver over dwell k_(dwell) and time frame n_(frame), and that havebeen substantively extracted from received environment by the FSdespreader (147); and except for the baseband demodulator (148) thatdemodulates the resultant substantively extracted baseband signalsprovided by the despreader (147). The baseband source signalstransmitted from the uplink transmitters must contain sufficientinformation to remove any ambiguities remaining in the despreader outputsignals.

Similarly, in another embodiment, the FS downlink receiver shown in FIG.35 is substantively similar to the CPDS downlink receiver shown in FIG.20, except that each received dwell is despread in an FS despreader(147) rather than a CPDS despreader (97), resulting in 1×L_(port) vectorFS despreader output signal sequences

{y_(R)(n_(smp); n_(slot))}_(n_(smp) = 0)^(N_(smp) − 1),comprising the L_(port) signals that are intended for the downlinkreceiver over time slot n_(slot), and that have been substantivelyextracted from received environment by the FS despreader (147); andexcept for the baseband demodulator (148) that demodulates the resultantsubstantively extracted baseband signals provided by the despreader(147). The baseband source signals transmitted from the uplinktransmitters must contain sufficient information to remove anyambiguities remaining in the despreader output signals,

As shown in FIG. 36, at the uplink despreader, dwell k_(dwell) isdespread over time frame n_(frame) by the sequential steps of:

-   -   Organizing the demultiplexer output signal sequence

{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1)  into  N_(smp) × N_(chp)  matrix  X_(R)(n_(frame), k_(dwell)),where N_(smp) is the number of received baseband samples per chip in thedwell at the demultiplexer output sampling rate (154), given by

$\begin{matrix}{X = \begin{pmatrix}{x(0)} & \ldots & {x\left( {N_{smp}\left( {N_{chp} - 1} \right)} \right)} \\\vdots & \ddots & \vdots \\{x\left( {N_{smp} - 1} \right)} & \ldots & {x\left( {{N_{smp}\left( {N_{chp} - 1} \right)} + N_{smp} - 1} \right)}\end{pmatrix}} & \left( {{Eq}\mspace{14mu} 19} \right)\end{matrix}$for general received data sequence

{x(n_(smp))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1).

-   -   Removing the receive spreading code (155) from        X_(R)(n_(frame),k_(dwell)), using algorithm

$\begin{matrix}\left. {X_{R}\left( {n_{frame},k_{frame}} \right)}\leftarrow{{X_{R}\left( {n_{frame},k_{frame}} \right)}{diag}\left\{ {c_{R}^{*}\left( {n_{frame},k_{frame}} \right)} \right\}} \right. & \left( {{Eq}\mspace{14mu} 20} \right)\end{matrix}$

-   -   where c_(R)(n_(frame),k_(dwell)) is the N_(chp)×1 receive        spreading code vector over dwell k_(dwell) and time frame        n_(frame), and where diag{•} is the vector-to-diagonal matrix        conversion operation and (•)* is the complex conjugation        operation.    -   Compute N_(smp)×L_(port) despread baseband signal matrix        Y_(R)(n_(frame),k_(dwell)), using linear signal separation        algorithm        Y _(R)(n _(frame) ,k _(dwell))=X _(R)(n _(frame) , k _(frame))W        _(R)(n _(frame) ,k _(dwell)),  (Eq21)    -   where W_(R)(n_(frame),k_(dwell)) is an N_(chp)×L_(port) linear        combining matrix.    -   Convert the despread baseband signal matrix        Y_(R)(n_(frame),k_(dwell)) back to a sequence of 1×L_(port)        despread baseband signal vectors

{y_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp) − 1)by applying an N_(smp):1 parallel-to-series (P/S) conversion operation(157) to each row of Y_(R)(n_(frame),k_(dwell)).

In one embodiment, the despreading operations performed in the downlinkFS despreader, shown in FIG. 37, are substantively equivalent to thoseshown in FIG. 36, except that they are only applied to time slots andfrequency channels monitored by the downlink receiver.

If the baseband signal sequence possesses structure that can beexploited in an adaptation algorithm, then the CPDS adaptation procedureshown in FIG. 23 can be used to directly compute the linear combiningmatrix W_(R)(n_(frame),k_(dwell)). For the exemplary FS transceiver andnetwork parameters described in Table 2, the baseband cyclic prefixintroduces self-coherence that can be exploited using theauto-self-coherence (auto-SCORE) algorithm described in U.S. Pat. No.7,079,480 entitled “Enhancing Security and Efficiency of WirelessCommunications through Structural Embedding,” by the present inventor.

If the spreading code is known except for an unknown frequency offset,then unstructured parameter estimation techniques that are well-known inthe art, such as Multiple Signal Classification (MUSIC), can be used todetect and determine the frequency offset of every signal using theknown receive spreading code, and equally well-known methods such aslinearly-constrained power minimization (LCPM) can be used to developlinear combiner weights that can extract those signals from the receivedenvironment.

If the spreading code length N_(chp) is much larger than the number ofsignals impinging on the receiver, e.g., at the downlink receiver in theexemplary environment, or in extreme long-range communication scenarioswhere the spreading gain of the modulation format is being used to raisethe signal-to-noise ratio (SNR) of the signal above a thermal noisefloor, then alternative methods that exploit the duality of the FS andMOS-DSSS spreading methods can be used to jointly detect and estimatesignals using the known receive spreading code using an FFT-LS algorithmapplied over a subset of the baseband signal samples. In this case, thereceive spreading gain is treated as the signal, and the baseband signalsamples are treated as the spreading code for purposes of signaldetection and frequency offset estimation. Once this step has beenaccomplished, then the true linear combiner weightsW_(R)(n_(frame),k_(dwell)) can be constructed using an LCPM algorithmfor each of the detected signals.

The extension of alternate FS spreading methods to transceiversemploying polarization/spatial diverse multi-element antenna arrays, andto macrodiverse reception methods, is straightforward. The FS methodshould be especially well suited to strongly-macrodiverse networks, asthe LCPM algorithm is not dependent on the time-bandwidth product of thebaseband.

In yet a further embodiment, the network selects a particularimplementation based on its strategic value, which is stronglyinfluenced by the desired tradeoff between Grade of Service (‘GoS’) andthe required Codec SINR (signal-to-interference-and-noise ratio). If thenetwork is using a fully-blind, least-squares despreader, then between10.5 dB and 15 dB required SINR, the performance change shifts; belowthat noise level the GoS rises as the number of hop channels decrease,so the best strategy is to minimize hops, which means spreading has astrong benefit. However, around 12-13 dB required SINR a ‘crossover’effect is experienced, after which the GoS drops as the number of hopchannels decrease, so the best strategy then becomes to maximize hops,which means there is no experienced benefit without scheduling. (Thismay be changed if the signalers are not experiencing the 1 bit/symbolShannon limit of transmission capacity.) If, however, the network isusing a Matched-Filter despreader (‘MF’), the changeover point issignificantly different; it occurs nearly at 0 dB require SINR. Underthese conditions an 8.6 dB Forward Error Correction (‘FEC’) coding gain(0.5 dB codec input SINR) is required before any ‘ad hoc’ MF spreadingprovides a benefit; while above this, there is no benefit to any MFspreading without FEC (so again, scheduling is required). An FEC can bepart of an error detection/correction decoder for a coded communicationsystem in which information bits are “encoded” with redundant paritybits at the transmitter, which are then used to detect and (moretypically) correct for errors in the received bits or signal

In one embodiment, the present description assumes the “code generation”process is the result of the hardware on which the method is effectedperforming operations outside the scope of the invention, in order toadd bits to the input information stream that can be used to detectpacket errors, and to correct for such errors if possible in the Symboldemodulator, which is also outside scope of the invention. The inventiondoes not necessarily enhance this process beyond the means for doing sowhich are obvious extensions of the approach to those experienced andskilled in the field(s) of this invention, but can allow suchenhancements to be added or incorporated.

In another embodiment, one possible feature of the present descriptionis that it provides a useable base on which further enhancements can bemore effectively deployed. One such specific further enhancement is theuse of macrodiverse solutions, particularly for the CPDS; and a furthersub-enhancement of that therein is a weakly macrodiverse solution wherethe SM can be demodulated at any DAP to provide later signalimprovement.

Additionally, in one embodiment, another possible feature of the presentdescription is that its use of a blind despreading algorithm renders thenetwork's communications interference-excising, creates far greatertolerance, and operates in conditions of greater variability of transmitpower ranges. Additionally, because the transmissions are ‘open loop’(no requirement for a return ‘ack’ or handshake) both power managementand signal feedback overheads are greatly simplified or reduced.

Still yet, in another embodiment, one possible feature of the presentdescription is that its flexible incorporation of CPDS cyclic prefixesat the symbol and chip level, and its instantiation over discretetime-frequency dwells, either with fixed time framing, or with ad hoctime slotting, allow it to be deployed over a wide range of frequencybands, and over a wider range of network topologies, transmissionranges, and use scenarios. While the parameters given in Table 1 for oneembodiment have been chosen to provide full compliance with FCC § 15.247requirements for intentional radiators in that band, and forpoint-to-multipoint cellular network topologies, long-rangetransmissions, and Smart Grid use scenarios, it should be recognizedthat the embodiments in the present description can be applied to:

-   -   other frequency bands, including ISM bands currently used for        802.11 wireless local area networks (WLAN's), 802.15 wireless        personal area networks (WPAN's), or cellular telephony networks,        or very low frequency bands used for near-field communications        (NFC);    -   White Spaces deployments where frequency channels are        dynamically and potentially noncontiguously allocated based on        spectrum availability in different geographical areas;    -   other network topologies, including ad hoc point-to-point        topologies, and mesh network topologies;    -   other transmission ranges, including extremely short ranges        consistent with WPAN's and NFC links;    -   other M2M use scenarios, including RFID, short-range medical        networks, embedded automotive networks, point-of-sale financial        transaction networks, and so on; and    -   heterogeneous cognitive networks where the modulation format is        software defined and reformatted on a dynamic basis for        different topologies and use scenarios;

In one embodiment, the alternate frame synchronous embodiment furtherenhances flexibility of the embodiments in the present description, byallowing the invention to be applied over extreme long ranges, e.g.,consistent with airborne and satellite communication networks, and byallowing the invention to be used with, or overlaid on top of,transceivers employing arbitrary baseband modulation formats, e.g., LTEcommunication networks.

In another embodiment of this invention, a further possible feature ofthe embodiments in the present description is that networks may beformed comprising devices capable of playing different roles, so anydevice may be serving as at least one Signaling Machine (‘SM’) and anyother device may be serving (at the same time) as one Data AggregationPoint (‘DAP’). This is possible with each device comprising at least oneantenna and one transceiver for exchanging wireless transmissions. Inthis embodiment the method will be comprising: incorporating into eachtransmission at each transceiver a Cyclic-Prefix Direct-Sequence(‘CPDS’) differentiator for that transmission, with time-channelizeddespreading at the receiver; fitting each transmission into a series offrames of Upload Transmissions (‘UpLink’) and Download Transmissions(‘DownLink’); transmitting from any device on any UpLink; and,transmitting from any device on any DownLink.

Any specific subset of the method may be effected through anycombination of hardware and software elements. Hardware elements alreadywell-known and standard to the state of the are include a wide range ofCentral Processing Units (CPUs), Linear Processing Units (LPUs), VectorProcessing Units (VPUs), and Signal Processing Units (SPUs), which inturn may comprise single, dual, quad, or higher combinations of lessersuch elements. Hardware elements also include both programmable andre-programmable floating-point gate arrays (FPGAs), application-specificintegrated circuits (ASICs), programmable read-only memory (PROM) units,erasable-and-programmable read-only memory (EPROM) units, andelectronically erasable-and-programmable read-only memory (EEPROM)units. The conversion between digital and analog, and analog anddigital, representations may be through DAC/ADC chips, circuitry, orother transformational means incorporating both hardware (transceivers,processors) and software elements. Accordingly all elements disclosed inthe present description must be understood as being capable of beingeffected in a hardware-only, physically transforming device. However, asno human has either a radio (or other electromagnetic) transceivercapabilities, or the capabilities of any of the speed, precision andcapacity of perception, comprehension, memorization, and continuingreal-time transformation of such signals as required to effectembodiments in the present description, even though some elements may beincorporated in software, and the method as a whole can be abstractlycomprehended by an individual human being, the method cannot be effectedby any human being without direct, physical, and continuing assistanceby an external device. Therefore the present description incorporatesall existing and yet-to-be-devised hardware elements which instantiateand process the digital signals using the method herein, known to thepresent state of the art or effected as functional equivalents to themethods and techniques disclosed herein.

Some of the above-described functions may be composed of instructions,or depend upon and use data, that are stored on storage media (e.g.,computer-readable medium). The instructions and/or data may be retrievedand executed by the processor. Some examples of storage media are memorydevices, tapes, disks, and the like. The instructions are operationalwhen executed by the processor to direct the processor to operate inaccord with the embodiments in the present description; and the data isused when it forms part of any instruction or result therefrom.

The terms “computer-readable storage medium” and “computer-readablestorage media” as used herein refer to any medium or media thatparticipate in providing instructions to a CPU for execution. Such mediacan take many forms, including, but not limited to, non-volatile (alsoknown as ‘static’ or ‘long-term’) media, volatile media and transmissionmedia. Non-volatile media include, for example, one or more optical ormagnetic disks, such as a fixed disk, or a hard drive. Volatile mediainclude dynamic memory, such as system RAM or transmission or bus‘buffers’. Common forms of computer-readable media include, for example,a floppy disk, a flexible disk, a hard disk, magnetic tape, any othermagnetic medium, a CD-ROM disk, digital video disk (DVD), any otheroptical medium, any other physical medium with patterns of marks orholes.

Memory, as used herein when referencing to computers, is the functionalhardware that for the period of use retains a specific structure whichcan be and is used by the computer to represent the coding, whether dataor instruction, which the computer uses to perform its function. Memorythus can be volatile or static, and be any of a RAM, a PROM, an EPROM,an EEPROM, a FLASHEPROM, any other memory chip or cartridge, a carrierwave, or any other medium from which a computer can read data,instructions, or both.

I/O, or ‘input/output’, is any means whereby the computer can exchangeinformation with the world external to the computer. This can include awired, wireless, acoustic, infrared, or other communications link(including specifically voice or data telephony); a keyboard, tablet,camera, video input, audio input, pen, or other sensor; and a display(2D or 3D, plasma, LED, CRT, tactile, or audio). That which allowsanother device, or a human, to interact with and exchange data with, orcontrol and command, a computer, is an I/O device, without which anycomputer (or human) is essentially in a solipsistic state.

The above description of the invention is illustrative and notrestrictive. Many variations of the disclosed embodiments may becomeapparent to those of skill in the art upon review of this disclosure.The scope of the embodiments of the present description should,therefore, be determined not with reference to the above description,but instead should be determined with reference to the appended claimsalong with their full scope of equivalents.

While the present description has been described chiefly in connectionwith one embodiment, these descriptions are not intended to limit thescope of any of the embodiments to the particular forms (whetherelements of any device or architecture, or steps of any method) setforth herein. It will be further understood that the elements or methodsof the disclosed embodiments are not necessarily limited to the discreteelements or steps, or the precise connectivity of the elements or orderof the steps described, particularly where elements or steps which arepart of the prior art are not referenced (and are not claimed). To thecontrary, the present descriptions are intended to cover suchalternatives, modifications, and equivalents as may be included withinthe spit and scope of the embodiments in the present description asdefined by the appended claims and otherwise appreciated by one ofordinary skill in the art.

I claim:
 1. A method for physically secure digital signal processing forwireless machine-to-machine (‘M2M)’) networks, said networks comprisingat least one set of transceivers comprising at least one SignalingMachine (‘SM’) and one Data Aggregation Point (‘DAP’) with each SM andDAP comprising at least one antenna and one transceiver for exchangingwireless transmissions, said method comprising: generating transmissioninformation that is: randomly varied at every transmitter in thenetwork: and, neither known to any receiver in, nor provisioned by, thenetwork: using that transmission information to directly spread a signalwith any baseband modulation format, thereby implementingdifferentiation between transmitters in the network by any of aspreading code and baseband signal samples; applying a timing advance toan intended uplink receiver; then fitting each transmission into aseries of frames of Upload Transmissions (‘UpLink’) and DownloadTransmissions (‘DownLink’); transmitting from any of, the SM on anUpLink and the DAP on a Downlink: and, despreading, at an intendedreceiver for that transmission, the received signal.
 2. The method as inclaim 1 further comprising: incorporating into each transmission at eachtransceiver a Frame-Synchronous (‘FS’) differentiator for thattransmission; and using time-channelized despreading at the intendeduplink receiver for that transmission.
 3. The method as in claim 2,wherein the step of using time-channelized despreading at the intendeduplink receiver for that transmission further comprises: using any ofsource spreading and receive spreading elements, baseband signalsamples, and known and exploitable structure from the transmissioninformation, to despread a demultiplexed uplink data sequence{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1)received in k_(dwell) over time frame n_(frame) by performing thesequential steps of: performing a 1:N_(smp)×N_(chp) serial-to-matrixconversion operation on the demultiplexer output signal sequence{x_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp)N_(chp) − 1),resulting in N_(smp)×N_(chp) matrix X_(R)(n_(frame),k_(dwell)); removingthe N_(chp)×1 receive spreading code c_(R)(n_(frame),k_(dwell)) fromX_(R)(n_(frame),k_(dwell)); computing N_(smp)×L_(port) despread basebandsignal matrix Y_(R)(n_(frame),k_(dwell)); and, converting the despreadbaseband signal matrix Y_(R)(n_(frame),k_(dwell)) back to a sequence of1×L_(port) despread baseband signal vectors{y_(R)(n_(smp); n_(frame), k_(dwell))}_(n_(smp) = 0)^(N_(smp) − 1) byapplying an N_(smp):1 parallel-to-series (P/S) conversion operation toeach row of Y_(R)(n_(frame),k_(dwell)).
 4. The method as in claim 1 forphysically secure digital signal processing for wireless M2M networks,further comprising implementing for each uplink transmission received atmultiple receivers receiving a signal from the same transmitter, aweakly-macrodiverse uplink despreading method.
 5. The method as in claim4, wherein the step of implementing for each uplink transmission aweakly-macrodiverse uplink despreading method further comprises:transmitting an uplink transmission from at least one user to a set ofmultiple receivers, at each member receiver detecting and substantivelydespreading that uplink transmission to a received signal; uploadingfrom each member receiver its respective detected and substantivelydespread received signal to a central site; associating the uploadedreceived signals at that central site; and, demodulating the uploadedreceived signals into the source symbols using a multidimensionaldemodulation algorithm.
 6. The method as in claim 1 for physicallysecure digital signal processing for wireless M2M networks, furthercomprising implementing for each uplink transmission received atmultiple receivers receiving a signal from the same transmitter, astrongly-macrodiverse uplink despreading method.
 7. The method as inclaim 6 wherein the step of implementing for each uplink transmission astrongly-macrodiverse uplink despreading method further comprises:transmitting an uplink transmission from at least one user to a set ofmultiple receivers; detecting and generating from the received uplinktransmission at each member receiver aM_(smp) × M_(sym)  DAP  data  matrix{X_(R)(n_(frame), k_(dwell); l_(R))}_(l_(R) = 1)^(L_(R));wherein, n_(frame) is time-frame, K_(dwell) is dwell index, X_(R) isreceived signal, and L_(R) is intended uplink receiver uploading to acentral processing site from each member receiver its respective DAPdata matrix; associating at that central processing site the uploadedDAP data matrices; and, demodulating the uploaded received signals intosource symbols using a multidimensional demodulation algorithm.
 8. Themethod as in claim 7, wherein the step of demodulating the uploadedreceived signals into the source symbols further comprises: stacking theassociated DAP data matrices into an L_(R)M_(smp)×M_(sym) network datamatrix X_(R)(n_(frame),k_(dwell)) given by${{X_{R}\left( {n_{frame},k_{dwell}} \right)} = \begin{pmatrix}{X_{R}\left( {n_{frame},{k_{dwell};1}} \right)} \\\vdots \\{X_{R}\left( {n_{frame},{k_{dwell};L_{R}}} \right)}\end{pmatrix}};$ passing the network data matrix to a network-leveldespreader that, on receiving and downconverting a symbol stream for anydevice removes if needed any DAP carrier offsets{α_(R)(l_(R))}_(l_(R) = 1)^(L_(R)); detects the sources {l_(S)}_(k′)_(dwell) _((l) _(S) _()=k) _(dwell) using that channel; estimates theircarrier offsets {α_(S)(l_(S))}_(k′) _(dwell) ; develops a set of linearcombiner weights with L_(R)M_(smp) degrees of freedom, and uses thosecombining weights to extract all of those member receivers' symbolstreams from the network data matrix, to be used by the network.
 9. Themethod as in claim 1, wherein the step of generating transmissioninformation that is randomly varied at every node in the network, andneither known to the receivers in the network nor provisioned by thenetwork, further comprises generating transmission information that isboth randomly varied amongst transmitters in the network and at everytransmitter is randomly varied over frames and dwells.
 10. The method asin claim 1, wherein the step of despreading, at the intended uplinkreceiver for that transmission, the received signal, further comprises:detecting all sources intended for the receiver; using those sources toestimate key parameters of those signals; using those key parameters todevelop linear combining weights that can substantively despread thosesignals; using those linear combining weights to produce despread sourcesymbols; and demodulating those despread source symbols.
 11. The methodas in claim 1, wherein the step of despreading, at the intended receiverfor that transmission, further comprises: detecting signals of interest(SOI's) to the intended receiver; estimating key parameters of thosesignals in which the baseband data takes on a role of a Cyclic-PrefixDirect-Sequence (CPDS) temporal signature vector; using the keyparameters to develop a set of linear combiner weights that extract theSOI baseband symbol streams and without knowledge of the content exciseany signals not of interest (SNOI's) to the intended receiver; computinga despread symbol matrix; computing despread symbols using the linearcombining weights; and, using demodulation and decryption to extractsource information from the despread symbols.
 12. The method as in claim1, wherein the step of despreading, at the intended receiver for thattransmission, further comprises: detecting signals of interest (SOI's)to the intended receiver; estimating key parameters of those signals inparticular their observed frequencies-of-arrival (FOA){α_(RS)(n_(hop); l)}_(l = 1)^(L_(port)), using a Fast FourierTransform-Least Squares (FFT-LS) algorithm applied to a subset of rowsof X_(R)(n_(hop)), in which the baseband data takes on a role of a CPDStemporal signature vector; developing a set of N_(chp)×L_(port) linearcombiner weights W_(R)(n_(hop)) that can extract the SOI baseband symbolstreams from X_(R)(n_(hop)), and without knowledge of the content exciseany signals not of interest (SNOI's) to the intended receiver; computingN_(smp)×L_(port) despread symbol matrixY_(R)(n_(hop))=X_(R)(n_(hop))W_(R)(n_(hop)); computing despread anddespun symbols, by substantively removing frequency offset on each rowof Y_(R)(n_(hop)) using the estimates of observed FOAs; and, usingdemodulation and decryption to extract source information from thedespread and despun symbols.